Výsledky vyhľadávania - multiobjective programming ((problemy OR problemas) OR problemys) with uncertain data~

Upresniť hľadanie
  1. 1
  2. 2

    Zdroj: Advances in Soft Computing ISBN: 9783540714408

  3. 3

    Popis súboru: 64 páginas; application/pdf

    Relation: ANALYTICS VIDHYA. Introductory guide on linear programming for (aspiring) data scientists [en línea]. 2017 [citado en noviembre de 2020]. Disponible en línea: https://www.analyticsvidhya.com/blog/2017/02/lintroductory-guide-on-linear-programming-explained-in-simple-english/.; ANONYMOUS. Logística almacenes Éxito [en línea]. 2014 [citado en noviembre de 2020]. Disponible en línea: https://almacenesexitologistica.blogspot.com/2014/05/logistica-almacenes-exito.html.; ARKANET. Logística [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: http://www.arkanet.mx/administrador/logistica.html.; BALCUCHO, José Alfredo y GUALDRÓN, Oscar Eduardo. Optimización de la base de reglas de un controlador difuso, mediante técnicas estocásticas como algoritmos genéticos y el simulated annealing. Revista Colombiana de Tecnologías de Avanzada [en línea]. 2010, vol.2, no.16 [citado en noviembre de 2020]. Disponible en línea: http://www.unipamplona.edu.co/unipamplona/portalIG/home_40/recursos/03_v13_18/revista_16/27102011/10.pdf.; BERNARDINO. Cross-docking: Funciones y Tipos [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: https://bernardinoabad.es/2019/07/26/cross-docking-funciones-y-tipos/.; BROWN, Ingrid Viviana; QUIROGA, Juan Pablo y GALLÓN, Fabián Andrés. Proyecto de trabajo de grado para el diseño de la red de valor para pescado fresco hacia las tiendas de CENCOSUD, Colombia en Cundinamarca. Trabajo de grado Especialista en Gerencia Logística en Redes de Negocios. Bogotá, D.C.; Universidad Piloto de. Colombia. Facultad de Administración de Empresas. Especialización en Gerencia Logística en Redes de Negocio, 2013; CHANG, Keliang; ZHOU, Hong; CHEN, Guijing y CHEN, Huiqin. Multiobjective location routing problem considering uncertain data after disasters. Discrete Dynamics in Nature and Society [en línea]. 2017, [citado en noviembre de 2020]. Disponible en línea: https://doi.org/10.1155/2017/1703608.; FARHAM, Mohammad Saleh; SRAL, Haldun y IYIGUN, Cem. A column generation approach for the location-routing problem with time windows. Computers and Operations Research [en linea]. 2018, vol.90 [citado en noviembre de 2020]. Disponible en línea: https://doi.org/10.1016/j.cor.2017.09.010.; GARCÍA, Lucero y BAEZA, Roberto Configuración de la cadena de suministros y la cadena de valor para una phyme. Verano de la investigación Científica [en línea]. 2017, vol.3, no.2 [citado en noviembre de 2020]. Disponible en línea: http://www.jovenesenlaciencia.ugto.mx/index.php/jovenesenlaciencia/article/view/2045/1539.; GESTAL, Marcos. Introducción a los algoritmos genéticos [en línea]. 2018 [citado en noviembre de 2020]. Disponible en internet: https://www.researchgate.net/publication/237812449_Introduccion_a_los_Algoritmos_Geneticos.; GUANGA, Alexander; MALAN, Mónica y ZUMBA, Jessica. Aplicación del método de ramificación y acotamiento en la empresa "Muebles Dormihogar" [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: https://es.slideshare.net/jessicazumba7/final-operativa; HANIK, Dean M. Industrial location theory. International Encyclopedia of Geography: People, the Earth, Environment and Technology [en línea]. 2017, vol.15 [citado en noviembre de 2020]. Disponible en línea: https://doi.org/10.1002/9781118786352.wbieg0216; KOÇ, Çağrı; BELTAŞ, Tolga; JABALIB, Ola; LAPORTE, Gilbert. The fleer size and mix location-routing problem with time windows: Formulation and a heuristic algorithm. European Journal of Operational Research [en línea]. 2016, vol.248, no.1 [citado en noviembre de 2020]. Disponible en línea: https://doi.org/10.1016/j.ejor.2015.06.082.; LINKPANG. Ramificación y poda [en línea]. s.f. [citado en noviembre de 2020]. Disponible en internet: https://es.linkfang.org/wiki/Ramificaci%C3%B3n_y_acotaci%C3%B3n.; MARKETING. La última frontera [en línea]. 2020 [citado en noviembre de 2020]. Disponible en línea: bit.ly/39DgObt.; MARTÍN-ANDINO, Ramón. Cadena de Suministro (SCM). Madrid: EOI Escuela de Negocios, 2006.; MOUJAHID, Abdelmalik; INAZA, Iñaki y LARRAÑAGA, Pedro. Tema 2. Alogoritmos genéticos [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: http://www.sc.ehu.es/ccwbayes/docencia/mmcc/docs/t2geneticos.pdf.; OBSERVATORIO DE LA EMPRESA MULTINACIONAL ESPAÑOLA [OEME]. Nota técnica: “Gestión de la cadena de suministros en un contexto de globalización” [en línea]. 2011 [citado en noviembre de 2020]. Disponible en línea: http://itemsweb.esade.es/research/oeme/notas/OEME-gestion-de-la-cadena-de-suministros.pdf.; RODRÍGUEZ, Edgar Guillermo. Identificación de prácticas en la gestión de la cadena de suministro sostenible para la industria alimenticia. Revista Científica Pensamiento y Gestión [en línea]. 2018, no.45 [citado en noviembre de 2020]. Disponible en línea: http://dx.doi.org/10.14482/pege.41.9704.; TQ CONFIABLE. Nosotros [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: https://www.tqconfiable.com/quienes-somos-home.; TQ CONFIABLE. TQ en Colombia [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: https://www.tqconfiable.com/crossdocking.; UN GEÓGRAFO SIN GEOGRAFÍA. La Expansión Geográfica de Wal-Mart [en línea]. 2014 [citado en noviembre de 2020]. Disponible en línea: https://ungeografosingeografia.blogspot.com/2014/07/la-expansion-geografica-de-wal-mart.html.; UNKNOWN. Cross Docking [en línea]. 2015 [citado en noviembre de 2020]. Disponible en línea: https://logisticaudea15.blogspot.com/2015/07/cross-docking-dada-la-busqueda-de-una.html.; VÁZQUEZ, Jair. Ingeniería en computación [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: http://ri.uaemex.mx/bitstream/handle/20.500.11799/70265/secme-32643_1.pdf;jsessionid=1F0049E6E764B360280FE7DEFE53F654?sequence=1.; WIKIPEDIA. Ramificación y poda [en línea]. s.f. [citado en noviembre de 2020]. Disponible en línea: https://es.wikipedia.org/wiki/Ramificaci%C3%B3n_y_poda.; WOGNUM, P. M.; BREMMERS, Harry; TRIENEKENS, Jacques H.; VAN DER VORST, Jack G. A. J. y BLOEMHOF, Jacqueline M. Systems for sustainability and transparency of food supply chains - Current status and challenges. Advanced Engineering Informatics [en línea]. 2011, vol.25 [citado en noviembre de 2020]. Disponible en línea: https://doi.org/10.1016/j.aei.2010.06.001.; https://hdl.handle.net/10983/25611

  4. 4

    Popis súboru: xvi, 174 páginas; application/pdf

    Relation: Abdul-Jalbar, B., Colebrook, M., Dorta-Guerra, R., & Gutiérrez, J. M. (2016). Centralized and decentralized inventory policies for a single-vendor two-buyer system with permissible delay in payments. Computers & Operations Research, 74, 187-195. https://doi.org/10.1016/j.cor.2016.04.030; Adam, N.-R. B., Dauhoo, M. Z., Khoodaruth, A. A. H., & Elahee, M. K. (2016). A two-stage stochastic programming optimisation for sugar-ethanol-electricity production from sugarcane: A case study of Mauritius. International Journal of Mathematical Modelling and Numerical Optimisation, 7(1), 20-32.; Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. European Journal of Operational Research, 196(1), 1-20. https://doi.org/10.1016/j.ejor.2008.02.014; Ahumada, O., & Villalobos, J. R. (2011). A tactical model for planning the production and distribution of fresh produce. Annals of Operations Research, 190(1), 339-358. https://doi.org/10.1007/s10479-009-0614-4; Alonso Pippo, W., Luengo, C. A., Alonsoamador Morales Alberteris, L., Garzone, P., & Cornacchia, G. (2011). Energy Recovery from Sugarcane-Trash in the Light of 2nd Generation Biofuel. Part 2: Socio-Economic Aspects and Techno-Economic Analysis. Waste and Biomass Valorization, 2(3), 257-266. https://doi.org/10.1007/s12649-011-9069-3; Alonso-Pippo, W., Luengo, C. A., Alonsoamador Morales Alberteris, L., García del Pino, G., & Duvoisin, S. (2013). Practical implementation of liquid biofuels: The transferability of the Brazilian experiences. Energy Policy, 60, 70-80. https://doi.org/10.1016/j.enpol.2013.04.038; Álvarez-Rodríguez, D. A., Normey-Rico, J. E., & Flesch, R. C. C. (2017). Model predictive control for inventory management in biomass manufacturing supply chains. International Journal of Production Research, 55(12), 3596-3608. https://doi.org/10.1080/00207543.2017.1315191; Amu, L.G., Garcia, J.A., Galvis , D.E., & Rubiano, O. (2013). Optimisation of harvest resources in a colombian sugar mill by use of simulation models. Proceedings of the International Society of Sugar Cane Technologists, 28, 2042-2049. http://bonsucro.com/site/wp-content/uploads/2013/02/ISSCT-Development-Bonsucro-Standard-Viart-N-and-Rein-P-2013.pdf; Asocaña. (2017). Más que azúcar, una fuente de energía renovable para el país. https://www.asocana.org/documentos/562017-ED2FFB51-00FF00,000A000,878787,C3C3C3,0F0F0F,B4B4B4,FF00FF,2D2D2D.pdf; Baghalian, A., Rezapour, S., & Farahani, R. Z. (2013). Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case. European Journal of Operational Research, 227(1), 199-215. https://doi.org/10.1016/j.ejor.2012.12.017; Ballou, R. H. (2007). Business logistics/supply chain management: Planning, organizing, and controlling the supply chain. Pearson Education India.; Banco Interamericano de Desarrollo (BID). (2012). “Evaluación del ciclo de vida de la cadena de producción de biocombustibles en Colombia”.; Barbosa-Póvoa, A. P., da Silva, C., & Carvalho, A. (2017). Opportunities and Challenges in Sustainable Supply Chain: An Operations Research Perspective. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2017.10.036; Barrett, C. B. (2021). Overcoming Global Food Security Challenges through Science and Solidarity. American Journal of Agricultural Economics, 103(2), 422-447. https://doi.org/10.1111/ajae.12160; Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2017). Agribusiness Supply Chain Risk Management: A Review of Quantitative Decision Models. Omega. https://doi.org/10.1016/j.omega.2017.07.005; Bekkering, J., Broekhuis, A. A., & van Gemert, W. J. T. (2010). Optimisation of a green gas supply chain – A review. Bioresource Technology, 101(2), 450-456. https://doi.org/10.1016/j.biortech.2009.08.106; Benoît, C., Norris, G. A., Valdivia, S., Ciroth, A., Moberg, A., Bos, U., Prakash, S., Ugaya, C., & Beck, T. (2010). The guidelines for social life cycle assessment of products: Just in time! The International Journal of Life Cycle Assessment, 15(2), 156-163. https://doi.org/10.1007/s11367-009-0147-8; Bertsimas, D., Farias, V. F., & Trichakis, N. (2011). The Price of Fairness. Operations Research, 59(1), 17-31. https://doi.org/10.1287/opre.1100.0865; Bezuidenhout, C. N., & Singels, A. (2007a). Operational forecasting of South African sugarcane production: Part 1 – System description. Agricultural Systems, 92(1), 23-38. https://doi.org/10.1016/j.agsy.2006.02.001; Bezuidenhout, C. N., & Singels, A. (2007b). Operational forecasting of South African sugarcane production: Part 2 – System evaluation. Agricultural Systems, 92(1), 39-51. https://doi.org/10.1016/j.agsy.2006.03.002; Birge, J. R., & Louveaux, F. (2011). Introduction to stochastic programming. Springer Science & Business Media.; Blanco, V., Carpente, L., Hinojosa, Y., & Puerto, J. (2010). Planning for Agricultural Forage Harvesters and Trucks: Model, Heuristics, and Case Study. Networks and Spatial Economics, 10(3), 321-343. https://doi.org/10.1007/s11067-009-9120-0; Bocca, F. F., & Rodrigues, L. H. A. (2016). The effect of tuning, feature engineering, and feature selection in data mining applied to rainfed sugarcane yield modelling. Computers and Electronics in Agriculture, 128, 67-76. https://doi.org/10.1016/j.compag.2016.08.015; Bojesen, M., Skov-Petersen, H., & Gylling, M. (2015). Forecasting the potential of Danish biogas production – Spatial representation of Markov chains. Biomass and Bioenergy, 81, 462-472. https://doi.org/10.1016/j.biombioe.2015.07.030; Borgonovo, E., Gatti, S., & Peccati, L. (2010). What drives value creation in investment projects? An application of sensitivity analysis to project finance transactions. European Journal of Operational Research, 205(1), 227-236. https://doi.org/10.1016/j.ejor.2009.12.006; Borodin, V., Bourtembourg, J., Hnaien, F., & Labadie, N. (2016). Handling uncertainty in agricultural supply chain management: A state of the art. European Journal of Operational Research, 254(2), 348-359. https://doi.org/10.1016/j.ejor.2016.03.057; Bot, P., van Donk, D. P., Pennink, B., & Simatupang, T. M. (2015). Uncertainties in the Bidirectional Biodiesel Supply Chain. Journal of Cleaner Production, 95, 174-183. https://doi.org/10.1016/j.jclepro.2015.02.064; Branco, J. E. H., Branco, D. H., de Aguiar, E. M., Caixeta Filho, J. V., & Rodrigues, L. (2019). Study of optimal locations for new sugarcane mills in Brazil: Application of a MINLP network equilibrium model. Biomass and Bioenergy, 127, 105249.; Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299-312. https://doi.org/10.1016/j.ejor.2013.09.032; Bubicz, M. E., Barbosa-Póvoa, A. P. F. D., & Carvalho, A. (2019). Incorporating social aspects in sustainable supply chains: Trends and future directions. Journal of Cleaner Production, 237, 117500. https://doi.org/10.1016/j.jclepro.2019.06.331; Budzianowski, W. M., & Postawa, K. (2016). Total Chain Integration of sustainable biorefinery systems. Applied Energy, 184, 1432-1446. https://doi.org/10.1016/j.apenergy.2016.06.050; Caixeta-Filho, J. V. (2006). Orange harvesting scheduling management: A case study. Journal of the Operational Research Society, 57(6), 637-642. https://doi.org/10.1057/palgrave.jors.2602041; Campos-Guzmán, V., García-Cáscales, M. S., Espinosa, N., & Urbina, A. (2019). Life Cycle Analysis with Multi-Criteria Decision Making: A review of approaches for the sustainability evaluation of renewable energy technologies. Renewable and Sustainable Energy Reviews, 104, 343-366. https://doi.org/10.1016/j.rser.2019.01.031; Cardoso, T. F., Chagas, M. F., Rivera, E. C., Cavalett, O., Morais, E. R., Geraldo, V. C., Braunbeck, O., da Cunha, M. P., Cortez, L. A. B., & Bonomi, A. (2015). A vertical integration simplified model for straw recovery as feedstock in sugarcane biorefineries. Biomass and Bioenergy, 81, 216-223. https://doi.org/10.1016/j.biombioe.2015.07.003; Carvajal, J., Sarache, W., & Costa, Y. (2019). Addressing a robust decision in the sugarcane supply chain: Introduction of a new agricultural investment project in Colombia. Computers and Electronics in Agriculture, 157, 77-89. https://doi.org/10.1016/j.compag.2018.12.030; Castaño, F., Rossi, A., Sevaux, M., & Velasco, N. (2014). A column generation approach to extend lifetime in wireless sensor networks with coverage and connectivity constraints. Computers & Operations Research, 52, 220-230.; Castaño, F., Velasco, N., & Carvajal, J. (2019). Content-Based Conference Scheduling Optimization. IEEE Latin America Transactions, 17(04), 597-606.; Chen, Y., Wang, S., Yao, J., Li, Y., & Yang, S. (2018). Socially responsible supplier selection and sustainable supply chain development: A combined approach of total interpretive structural modeling and fuzzy analytic network process. Business Strategy and the Environment, 27(8), 1708-1719. https://doi.org/10.1002/bse.2236; Colin, E. C. (2009). Mathematical programming accelerates implementation of agro-industrial sugarcane complex. European Journal of Operational Research, 199(1), 232-235. https://doi.org/10.1016/j.ejor.2008.11.016; Congreso de Colombia. (2014). LEY 1715 DE 2014 Diario Oficial No. 49.150. Bogotá, DC: Imprenta Nacional. Retrieved, 9, 2017.; Congreso de Colombia. (2019). LEY 1955 DE 2019, Plan Nacional de Desarrollo 2018-2022. “Pacto por Colombia, Pacto por la Equidad”. http://www.suin-juriscol.gov.co/viewDocument.asp?ruta=Leyes/30036488; Costa, A. M., dos Santos, L. M. R., Alem, D. J., & Santos, R. H. S. (2011). Sustainable vegetable crop supply problem with perishable stocks. Annals of Operations Research. https://doi.org/10.1007/s10479-010-0830-y; Council of Supply Chain Management Professionals, CSCMP. (2017). CSCMP Supply Chain Management Definitions and Glossary.; da Silva, A. F., & Marins, F. A. S. (2014). A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill. Energy Economics, 45, 196-204. https://doi.org/10.1016/j.eneco.2014.07.005; da Silva, A. F., Marins, F. A. S., & Dias, E. X. (2015). Addressing uncertainty in sugarcane harvest planning through a revised multi-choice goal programming model. Applied Mathematical Modelling, 39(18), 5540-5558. https://doi.org/10.1016/j.apm.2015.01.007; Darby-Dowman, K., Barker, S., Audsley, E., & Parsons, D. (2000). A two-stage stochastic programming with recourse model for determining robust planting plans in horticulture. Journal of the Operational Research Society, 51(1), 83-89. https://doi.org/10.1057/palgrave.jors.2600858; Das, R., Shaw, K., & Irfan, Mohd. (2020). Supply chain network design considering carbon footprint, water footprint, supplier’s social risk, solid waste, and service level under the uncertain condition. Clean Technologies and Environmental Policy, 22(2), 337-370. https://doi.org/10.1007/s10098-019-01785-y; Davis, K. F., Gephart, J. A., Emery, K. A., Leach, A. M., Galloway, J. N., & D’Odorico, P. (2016). Meeting future food demand with current agricultural resources. Global Environmental Change, 39, 125-132. https://doi.org/10.1016/j.gloenvcha.2016.05.004; De Oliveira Florentino, H., De Lima, A. D., De Carvalho, L. R., Balbo, A. R., & Homem, T. P. D. (2011). Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration. International Transactions in Operational Research, 18(5), 605-615. https://doi.org/10.1111/j.1475-3995.2011.00818.x; de Oliveira Florentino, H., & Pato, M. V. (2014). A bi-objective genetic approach for the selection of sugarcane varieties to comply with environmental and economic requirements. Journal of the Operational Research Society, 65(6), 842-854. https://doi.org/10.1057/jors.2013.21; de Oliveira Florentino, H., & Pereira Sartori, M. M. (2003). Game theory in sugarcane crop residue and available energy optimization. Biomass and Bioenergy, 25(1), 29-34. https://doi.org/10.1016/S0961-9534(02)00189-7; de Souza Dias, M. O., Maciel Filho, R., Mantelatto, P. E., Cavalett, O., Rossell, C. E. V., Bonomi, A., & Leal, M. R. L. V. (2015). Sugarcane processing for ethanol and sugar in Brazil. Environmental Development, 15, 35-51.; Departamento Nacional de Planeación. (2008). Lineamientos de politica para promover la produccion sostenible de biocombustibles en Colombia (Documento CONPES 3510). DNP Bogotá, Colombia.; dos Reis Ferreira, R. A., da Silva Meireles, C., Assunção, R. M. N., Barrozo, M. A. S., & Soares, R. R. (2020). Optimization of the oxidative fast pyrolysis process of sugarcane straw by TGA and DSC analyses. Biomass and Bioenergy, 134, 105456.; Du, C., Dias, L. C., & Freire, F. (2019). Robust multi-criteria weighting in comparative LCA and S-LCA: A case study of sugarcane production in Brazil. Journal of Cleaner Production, 218, 708-717. https://doi.org/10.1016/j.jclepro.2019.02.035; Dunford, R. W., Marti, C. E., & Mittelhammer, R. C. (1985). A Case Study of Rural Land Prices at the Urban Fringe Including Subjective Buyer Expectations. Land Economics, 61(1), 10. https://doi.org/10.2307/3146135; Ebadian, M., van Dyk, S., McMillan, J. D., & Saddler, J. (2020). Biofuels policies that have encouraged their production and use: An international perspective. Energy Policy, 147, 111906. https://doi.org/10.1016/j.enpol.2020.111906; Eizenberg, E., & Jabareen, Y. (2017). Social Sustainability: A New Conceptual Framework. Sustainability, 9(1), 68. https://doi.org/10.3390/su9010068; El Espectador. (2021, septiembre 20). ELESPECTADOR.COM. ELESPECTADOR.COM. https://www.elespectador.com/judicial/megaproyecto-de-produccion-de-etanol-el-alcaravan-fue-un-fracaso-contraloria/; Elkington, J. (1997). Cannibals with forks. The triple bottom line of 21st century, 73.; Eskandarpour, M., Dejax, P., Miemczyk, J., & Péton, O. (2015). Sustainable supply chain network design: An optimization-oriented review. Omega, 54, 11-32. https://doi.org/10.1016/j.omega.2015.01.006; Espinoza-Pérez, A. T., Camargo, M., Narváez-Rincón, P. C., & Alfaro-Marchant, M. (2017). Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis. Renewable and Sustainable Energy Reviews, 69, 350-359. https://doi.org/10.1016/j.rser.2016.11.084; Esteso, A., Alemany, M. M. E., & Ortiz, A. (2018). Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. International Journal of Production Research, 56(13), 4418-4446. https://doi.org/10.1080/00207543.2018.1447706; Fahimnia, B., Sarkis, J., & Davarzani, H. (2015). Green supply chain management: A review and bibliometric analysis. International Journal of Production Economics, 162, 101-114. https://doi.org/10.1016/j.ijpe.2015.01.003; Farahani, R. Z., Hekmatfar, M., Fahimnia, B., & Kazemzadeh, N. (2014). Hierarchical facility location problem: Models, classifications, techniques, and applications. Computers & Industrial Engineering, 68, 104-117. https://doi.org/10.1016/j.cie.2013.12.005; Faria, L. F. F., Silva, J. E. A. R., Faria, L. F. F., & Silva, J. E. A. R. (2015). Effects of maintenance management procedures in sugarcane mechanic harvesting system equipment. Engenharia Agrícola, 35(6), 1187-1197. https://doi.org/10.1590/1809-4430-Eng.Agric.v35n6p1187-1197/2015; Fathollahi-Fard, A. M., Hajiaghaei-Keshteli, M., & Mirjalili, S. (2018). Multi-objective stochastic closed-loop supply chain network design with social considerations. Applied Soft Computing, 71, 505-525. https://doi.org/10.1016/j.asoc.2018.07.025; Fattahi, M., & Govindan, K. (2018). A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study. Transportation Research Part E: Logistics and Transportation Review, 118, 534-567. https://doi.org/10.1016/j.tre.2018.08.008; Fedebiocombustibles. (2021, enero 1). Federación Nacional de Biocombustibles de Colombia, Marco Normativo de los biocombustibles en Colombia. fedebiocombustibles.com. http://www.fedebiocombustibles.com/v3/estadistica-mostrar_info-titulo-Alcohol_Carburante_(Etanol).htm; Florentino, H. de O., Irawan, C., Aliano, A. F., Jones, D. F., Cantane, D. R., & Nervis, J. J. (2018). A multiple objective methodology for sugarcane harvest management with varying maturation periods. Annals of Operations Research, 267(1-2), 153-177. https://doi.org/10.1007/s10479-017-2568-2; Florentino, H. de O., Jones, D. F., Irawan, C. A., Ouelhadj, D., Khosravi, B., & Cantane, D. R. (2020). An optimization model for combined selecting, planting and harvesting sugarcane varieties. Annals of Operations Research. https://doi.org/10.1007/s10479-020-03610-y; Florio, M., & Colautti, S. (2005). A logistic growth theory of public expenditures: A study of five countries over 100 years. Public Choice, 122(3-4), 355-393. https://doi.org/10.1007/s11127-005-3900-y; Furlan, F. F., Costa, C. B. B., de Castro Fonseca, G., de Pelegrini Soares, R., Secchi, A. R., da Cruz, A. J. G., & de Campos Giordano, R. (2012). Assessing the production of first and second generation bioethanol from sugarcane through the integration of global optimization and process detailed modeling. Computers & Chemical Engineering, 43, 1-9.; Gao, J., & You, F. (2019). A stochastic game theoretic framework for decentralized optimization of multi-stakeholder supply chains under uncertainty. Computers & Chemical Engineering, 122, 31-46. https://doi.org/10.1016/j.compchemeng.2018.05.016; Gatti, S. (2013). Project finance in theory and practice: Designing, structuring, and financing private and public projects. Academic Press.; Ghaderi, H., Pishvaee, M. S., & Moini, A. (2016). Biomass supply chain network design: An optimization-oriented review and analysis. Industrial Crops and Products, 94, 972-1000. https://doi.org/10.1016/j.indcrop.2016.09.027; Gheewala, S., Silalertruksa, T., Nilsalab, P., Mungkung, R., Perret, S., & Chaiyawannakarn, N. (2014). Water Footprint and Impact of Water Consumption for Food, Feed, Fuel Crops Production in Thailand. Water, 6(6), 1698-1718. https://doi.org/10.3390/w6061698; Giannakis, M., & Papadopoulos, T. (2016). Supply chain sustainability: A risk management approach. International Journal of Production Economics, 171, 455-470. https://doi.org/10.1016/j.ijpe.2015.06.032; Gilani, H., & Sahebi, H. (2020). A multi-objective robust optimization model to design sustainable sugarcane-to-biofuel supply network: The case of study. Biomass Conversion and Biorefinery. https://doi.org/10.1007/s13399-020-00639-8; Gnansounou, E., Pachón, E. R., Sinsin, B., Teka, O., Togbé, E., & Mahamane, A. (2020). Using agricultural residues for sustainable transportation biofuels in 2050: Case of West Africa. Bioresource Technology, 305, 123080. https://doi.org/10.1016/j.biortech.2020.123080; Gobierno Digital Colombia. (2018). Datos abiertos Ministerio de Minas y energia Colombia. https://www.datos.gov.co/Minas-y-Energ-a/Tarifas-aplicadas-de-Gas-Natural/ek3f-5wn4/data; Govindan, K., Fattahi, M., & Keyvanshokooh, E. (2017). Supply chain network design under uncertainty: A comprehensive review and future research directions. European Journal of Operational Research, 263(1), 108-141. https://doi.org/10.1016/j.ejor.2017.04.009; Govindan, K., Shaw, M., & Majumdar, A. (2020). Social Sustainability Tensions in Multi-tier Supply Chain: A Systematic Literature Review towards Conceptual Framework Development. Journal of Cleaner Production, 123075. https://doi.org/10.1016/j.jclepro.2020.123075; Grimsey, D., & Lewis, M. (2007). Public private partnerships: The worldwide revolution in infrastructure provision and project finance. Edward Elgar Publishing.; Grunow, M., Günther, H.-O., & Westinner, R. (2007). Supply optimization for the production of raw sugar. International Journal of Production Economics, 110(1-2), 224-239. https://doi.org/10.1016/j.ijpe.2007.02.019; Guo, M., van Dam, K. H., Touhami, N. O., Nguyen, R., Delval, F., Jamieson, C., & Shah, N. (2020). Multi-level system modelling of the resource-food-bioenergy nexus in the global south. Energy, 197, 117196. https://doi.org/10.1016/j.energy.2020.117196; Haberl, H., Wackernagel, M., & Wrbka, T. (2004). Land use and sustainability indicators. An introduction. Land Use Policy, 21(3), 193-198. https://doi.org/10.1016/j.landusepol.2003.10.004; Hahn, M. H., & Ribeiro, R. V. (1999). Heuristic guided simulator for the operational planning of the transport of sugar cane. Journal of the Operational Research Society, 50(5), 451-459.; Haj Hasan, A., & Avami, A. (2018). Comparative assessment of bioethanol supply chain: Insights from Iran. Biofuels, 1-9. https://doi.org/10.1080/17597269.2018.1496385; Hall, J., Matos, S., & Silvestre, B. (2012). Understanding why firms should invest in sustainable supply chains: A complexity approach. International Journal of Production Research, 50(5), 1332-1348. https://doi.org/10.1080/00207543.2011.571930; Hasani, A., & Khosrojerdi, A. (2016). Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review, 87, 20-52. https://doi.org/10.1016/j.tre.2015.12.009; Henao, R., Sarache, W., & Gómez, I. (2019). Lean manufacturing and sustainable performance: Trends and future challenges. Journal of Cleaner Production, 208, 99-116. https://doi.org/10.1016/j.jclepro.2018.10.116; Henao, R., Sarache, W., & Gomez, I. (2021). A social performance metrics framework for sustainable manufacturing. International Journal of Industrial and Systems Engineering, 38(2), 167-197.; Higgins, A. (2006). Scheduling of road vehicles in sugarcane transport: A case study at an Australian sugar mill. European Journal of Operational Research, 170(3), 987-1000. https://doi.org/10.1016/j.ejor.2004.07.055; Higgins, A., Antony, G., Sandell, G., Davies, I., Prestwidge, D., & Andrew, B. (2004). A framework for integrating a complex harvesting and transport system for sugar production. Agricultural Systems, 82(2), 99-115. https://doi.org/10.1016/j.agsy.2003.12.004; Higgins, A., & Davies, I. (2005). A simulation model for capacity planning in sugarcane transport. Computers and Electronics in Agriculture, 47(2), 85-102. https://doi.org/10.1016/j.compag.2004.10.006; Higgins, A. J. (1999). Optimizing cane supply decisions within a sugar mill region. Journal of Scheduling, 2(5), 229-244.; Higgins, A. J. (2002). Australian Sugar Mills Optimize Harvester Rosters to Improve Production. Interfaces, 32(3), 15-25. https://doi.org/10.1287/inte.32.3.15.41; Higgins, A. J., & Laredo, L. A. (2006). Improving harvesting and transport planning within a sugar value chain. Journal of the Operational Research Society, 57(4), 367-376. https://doi.org/10.1057/palgrave.jors.2602024; Higgins, A. J., & Muchow, R. C. (2003). Assessing the potential benefits of alternative cane supply arrangements in the Australian sugar industry. Agricultural Systems, 76(2), 623-638.; Higgins, A., Muchow, R. C., Rudd, A. V., & Ford, A. W. (1998). Optimising harvest date in sugar production: A case study for the Mossman mill region in Australia I. Development of operations research model and solution. Field Crops Research, 57, 153-162.; Higgins, A., Thorburn, P., Archer, A., & Jakku, E. (2007). Opportunities for value chain research in sugar industries. Agricultural Systems, 94(3), 611-621. https://doi.org/10.1016/j.agsy.2007.02.011; Hua, Z., Jun, L., Zhaonian, Y., Sanji, G., Yingying, Y., & Zhaoli, L. (2013). Agronomic techniques to sugarcane mechanical seeding [J]. Journal of Chinese Agricultural Mechanization, 1, 020.; Huijbregts, M. A. J., Steinmann, Z. J. N., Elshout, P. M. F., Stam, G., Verones, F., Vieira, M., Zijp, M., Hollander, A., & van Zelm, R. (2017). ReCiPe2016: A harmonised life cycle impact assessment method at midpoint and endpoint level. The International Journal of Life Cycle Assessment, 22(2), 138-147. https://doi.org/10.1007/s11367-016-1246-y; Illukpitiya, P., Yanagida, J. F., Ogoshi, R., & Uehara, G. (2013). Sugar-ethanol-electricity co-generation in Hawai’i: An application of linear programming (LP) for optimizing strategies. Biomass and Bioenergy, 48, 203-212. https://doi.org/10.1016/j.biombioe.2012.11.003; J. W. Mishoe, J. W. Jones, & G. J. Gascho. (1979). Harvesting Scheduling of Sugarcane for Optimum Biomass Production. Transactions of the ASAE, 22(6), 1299-1304. https://doi.org/10.13031/2013.35202; Jaehn, F. (2016). Sustainable Operations. European Journal of Operational Research, 253(2), 243-264. https://doi.org/10.1016/j.ejor.2016.02.046; Jahani, H., Abbasi, B., & Talluri, S. (2019). Supply Chain Network Redesign: A Technical Note on Optimising Financial Performance. Decision Sciences, deci.12374. https://doi.org/10.1111/deci.12374; Jena, S. D., & Poggi, M. (2013). Harvest planning in the Brazilian sugar cane industry via mixed integer programming. European Journal of Operational Research, 230(2), 374-384. https://doi.org/10.1016/j.ejor.2013.04.011; Jiao, Z., Higgins, A. J., & Prestwidge, D. B. (2005). An integrated statistical and optimisation approach to increasing sugar production within a mill region. Computers and Electronics in Agriculture, 48(2), 170-181. https://doi.org/10.1016/j.compag.2005.03.004; Jin, S., Jeong, S., & Kim, K. (2017). A Linkage Model of Supply Chain Operation and Financial Performance for Economic Sustainability of Firm. Sustainability, 9(1), 139. https://doi.org/10.3390/su9010139; Joelsson, E., Erdei, B., Galbe, M., & Wallberg, O. (2016). Techno-economic evaluation of integrated first- and second-generation ethanol production from grain and straw. Biotechnology for Biofuels, 9, 1. https://doi.org/10.1186/s13068-015-0423-8; Jonker, J. G. G., Junginger, H. M., Verstegen, J. A., Lin, T., Rodríguez, L. F., Ting, K. C., Faaij, A. P. C., & van der Hilst, F. (2016). Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil. Applied Energy, 173, 494-510. https://doi.org/10.1016/j.apenergy.2016.04.069; Junqueira, R. de Á. R., & Morabito, R. (2019). Modeling and solving a sugarcane harvest front scheduling problem. International Journal of Production Economics, 213, 150-160.; Karp, S. G., Medina, J. D. C., Letti, L. A. J., Woiciechowski, A. L., de Carvalho, J. C., Schmitt, C. C., de Oliveira Penha, R., Kumlehn, G. S., & Soccol, C. R. (2021). Bioeconomy and biofuels: The case of sugarcane ethanol in Brazil. Biofuels, Bioproducts and Biorefining, n/a(n/a). https://doi.org/10.1002/bbb.2195; Khamjan, W., Khamjan, S., & Pathumnakul, S. (2013). Determination of the locations and capacities of sugar cane loading stations in Thailand. Computers & Industrial Engineering, 66(4), 663-674. https://doi.org/10.1016/j.cie.2013.09.006; Khan, S. A. R., Yu, Z., Golpira, H., Sharif, A., & Mardani, A. (2021). A state-of-the-art review and meta-analysis on sustainable supply chain management: Future research directions. Journal of Cleaner Production, 278, 123357. https://doi.org/10.1016/j.jclepro.2020.123357; Khatiwada, D., Leduc, S., Silveira, S., & McCallum, I. (2016). Optimizing ethanol and bioelectricity production in sugarcane biorefineries in Brazil. Renewable Energy, 85, 371-386. https://doi.org/10.1016/j.renene.2015.06.009; Kittilertpaisan, K., & Pathumnakul, S. (2017). Integrating a multiple crop year routing design for sugarcane harvesters to plant a new crop. Computers and Electronics in Agriculture, 136, 58-70. https://doi.org/10.1016/j.compag.2017.03.001; Kostin, A. M., Guillén-Gosálbez, G., Mele, F. D., Bagajewicz, M. J., & Jiménez, L. (2010). Integrating pricing policies in the strategic planning of supply chains: A case study of the sugar cane industry in Argentina. En S. Pierucci & G. B. Ferraris (Eds.), Computer Aided Chemical Engineering (Vol. 28, pp. 103-108). Elsevier. https://doi.org/10.1016/S1570-7946(10)28018-5; Kostin, A. M., Guillén-Gosálbez, G., Mele, F. D., Bagajewicz, M. J., & Jiménez, L. (2011). A novel rolling horizon strategy for the strategic planning of supply chains. Application to the sugar cane industry of Argentina. Computers & Chemical Engineering, 35(11), 2540-2563. https://doi.org/10.1016/j.compchemeng.2011.04.006; Kostin, A. M., Guillén-Gosálbez, G., Mele, F. D., Bagajewicz, M. J., & Jiménez, L. (2012). Design and planning of infrastructures for bioethanol and sugar production under demand uncertainty. Chemical Engineering Research and Design, 90(3), 359-376. https://doi.org/10.1016/j.cherd.2011.07.013; Kravanja, Z., & Čuček, L. (2013). Multi-objective optimisation for generating sustainable solutions considering total effects on the environment. Applied Energy, 101, 67-80. https://doi.org/10.1016/j.apenergy.2012.04.025; Kulkarni, V. G. (2016). Modeling and analysis of stochastic systems. Chapman and Hall/CRC.; Kumar, N., Patel, S. S., Chalodia, A. L., Vadaviya, O. U., Pandya, H. R., Pisal, R. R., Dakhore, K. K., & Patel, M. L. (2015). Markov chain and incomplete Gamma distribution analysis of weekly rainfall over Navsari region of south Gujarat. Mausam, 10.; Kusumastuti, R. D., Donk, D. P. van, & Teunter, R. (2016). Crop-related harvesting and processing planning: A review. International Journal of Production Economics, 174, 76-92. https://doi.org/10.1016/j.ijpe.2016.01.010; Le Gal, P.-Y., Le Masson, J., Bezuidenhout, C. N., & Lagrange, L. F. (2009). Coupled modelling of sugarcane supply planning and logistics as a management tool. Computers and Electronics in Agriculture, 68(2), 168-177. https://doi.org/10.1016/j.compag.2009.05.006; Le Gal, P.-Y., Lyne, P. W. L., Meyer, E., & Soler, L.-G. (2008). Impact of sugarcane supply scheduling on mill sugar production: A South African case study. Agricultural Systems, 96(1), 64-74. https://doi.org/10.1016/j.agsy.2007.05.006; Leduc, S., Starfelt, F., Dotzauer, E., Kindermann, G., McCallum, I., Obersteiner, M., & Lundgren, J. (2010). Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy, 35(6), 2709-2716. https://doi.org/10.1016/j.energy.2009.07.018; Lejars, C., Le Gal, P.-Y., & Auzoux, S. (2008). A decision support approach for cane supply management within a sugar mill area. Computers and Electronics in Agriculture, 60(2), 239-249. https://doi.org/10.1016/j.compag.2007.08.008; Liobikiene, G., Balezentis, T., Streimikiene, D., & Chen, X. (2019). Evaluation of bioeconomy in the context of strong sustainability. Sustainable Development, 27(5), 955-964. https://doi.org/10.1002/sd.1984; Liu, L., Parlar, M., & Zhu, S. X. (2007). Pricing and Lead Time Decisions in Decentralized Supply Chains. Management Science, 53(5), 713-725. https://doi.org/10.1287/mnsc.1060.0653; Liu, S., & Papageorgiou, L. G. (2018). Fair profit distribution in multi-echelon supply chains via transfer prices. Omega, 80, 77-94. https://doi.org/10.1016/j.omega.2017.08.010; Londoño, L. (2017). Desempeño de la Agroindustria de la Caña en Colombia 2016-2017, Performance of the Agroindustry of the Sugarcane in Colombia 2016-2017 (pp. 1-32). http://www.asocana.org//documentos/2452017.pdf; Longinidis, P., & Georgiadis, M. C. (2011). Integration of financial statement analysis in the optimal design of supply chain networks under demand uncertainty. International Journal of Production Economics, 129(2), 262-276. https://doi.org/10.1016/j.ijpe.2010.10.018; Longinidis, P., & Georgiadis, M. C. (2013). Managing the trade-offs between financial performance and credit solvency in the optimal design of supply chain networks under economic uncertainty. Computers & Chemical Engineering, 48, 264-279. https://doi.org/10.1016/j.compchemeng.2012.09.019; Longinidis, P., & Georgiadis, M. C. (2014). Integration of sale and leaseback in the optimal design of supply chain networks. Omega, 47, 73-89. https://doi.org/10.1016/j.omega.2013.08.004; Longinidis, P., Georgiadis, M. C., & Kozanidis, G. (2015). Integrating Operational Hedging of Exchange Rate Risk in the Optimal Design of Global Supply Chain Networks. Industrial & Engineering Chemistry Research, 54(24), 6311-6325. https://doi.org/10.1021/acs.iecr.5b00349; Lopez Milan, E., Miquel Fernandez, S., & Pla Aragones, L. M. (2006). Sugar cane transportation in Cuba, a case study. European Journal of Operational Research, 174(1), 374-386. https://doi.org/10.1016/j.ejor.2005.01.028; Lowe, T. J., & Preckel, P. V. (2004). Decision Technologies for Agribusiness Problems: A Brief Review of Selected Literature and a Call for Research. Manufacturing & Service Operations Management, 6(3), 201-208. https://doi.org/10.1287/msom.1040.0051; Macowski, D. H., Bonfim-Rocha, L., Orgeda, R., Camilo, R., & Ravagnani, M. A. S. S. (2020). Multi-objective optimization of the Brazilian industrial sugarcane scenario: A profitable and ecological approach. Clean Technologies and Environmental Policy, 22(3), 591-611. https://doi.org/10.1007/s10098-019-01802-0; Mallawaarachchi, T., & Quiggin, J. (2001). Modelling socially optimal land allocations for sugar cane growing in North Queensland: A linked mathematical programming and choice modelling study. Australian Journal of Agricultural and Resource Economics, 45(3), 383-409. https://doi.org/10.1111/1467-8489.00149; Marin, F., Jones, J. W., & Boote, K. J. (2017). A Stochastic Method for Crop Models: Including Uncertainty in a Sugarcane Model. Agronomy Journal, 109(2), 483. https://doi.org/10.2134/agronj2016.02.0103; Martínez-Guido, SergioI., Betzabe González-Campos, J., Ponce-Ortega, JoséM., Nápoles-Rivera, F., & El-Halwagi, MahmoudM. (2016). Optimal reconfiguration of a sugar cane industry to yield an integrated biorefinery. Clean Technologies and Environmental Policy, 18(2), 553-562. https://doi.org/10.1007/s10098-015-1039-1; Martinez-Hernandez, E. (2017). Trends in sustainable process design—From molecular to global scales. Current Opinion in Chemical Engineering, 17, 35-41. https://doi.org/10.1016/j.coche.2017.05.005; Matindi, R., Masoud, M., Hobson, P., Kent, G., & Liu, S. Q. (2018). Harvesting and transport operations to optimise biomass supply chain and industrial biorefinery processes. International Journal of Industrial Engineering Computations, 265-288. https://doi.org/10.5267/j.ijiec.2017.9.001; Matis, J. H., Saito, T., Grant, W. E., Iwig, W. C., & Ritchie, J. T. (1985). A Markov chain approach to crop yield forecasting. Agricultural Systems, 18(3), 171-187. https://doi.org/10.1016/0308-521X(85)90030-7; Maxwell, D., & van der Vorst, R. (2003). Developing sustainable products and services. Journal of Cleaner Production, 11(8), 883-895. https://doi.org/10.1016/S0959-6526(02)00164-6; Meemken, E.-M., Barrett, C. B., Michelson, H. C., Qaim, M., Reardon, T., & Sellare, J. (2021). Sustainability standards in global agrifood supply chains. Nature Food, 2(10), 758-765. https://doi.org/10.1038/s43016-021-00360-3; Mele, F. D., Kostin, A. M., Guillén-Gosálbez, G., & Jiménez, L. (2011). Multiobjective Model for More Sustainable Fuel Supply Chains. A Case Study of the Sugar Cane Industry in Argentina. Industrial & Engineering Chemistry Research, 50(9), 4939-4958. https://doi.org/10.1021/ie101400g; Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, 196(2), 401-412. https://doi.org/10.1016/j.ejor.2008.05.007; Messmann, L., Zender, V., Thorenz, A., & Tuma, A. (2020). How to quantify social impacts in strategic supply chain optimization: State of the art. Journal of Cleaner Production, 257, 120459. https://doi.org/10.1016/j.jclepro.2020.120459; Meza-Palacios, R., Aguilar-Lasserre, A. A., Morales-Mendoza, L. F., Pérez-Gallardo, J. R., Rico-Contreras, J. O., & Avarado-Lassman, A. (2019). Life cycle assessment of cane sugar production: The environmental contribution to human health, climate change, ecosystem quality and resources in México. Journal of Environmental Science and Health, Part A, 54(7), 668-678. https://doi.org/10.1080/10934529.2019.1579537; Ministerio de Ciencia, Tecnología e Innovación. (2019). Descripción de focos y líneas de investigación. https://minciencias.gov.co/sites/default/files/upload/convocatoria/anexo_1._descripcion_de_focos_y_lineas_de_investigacion.pdf; Ministerio Minas y Energía. (2018). Resolución 40185. República de Colombia.; Mohammadi, A., Abbasi, A., Alimohammadlou, M., Eghtesadifard, M., & Khalifeh, M. (2017). Optimal design of a multi-echelon supply chain in a system thinking framework: An integrated financial-operational approach. Computers & Industrial Engineering, 114, 297-315. https://doi.org/10.1016/j.cie.2017.10.019; Morales Chávez, M. M., Sarache, W., & Costa, Y. (2018). Towards a comprehensive model of a biofuel supply chain optimization from coffee crop residues. Transportation Research Part E: Logistics and Transportation Review, 116, 136-162. https://doi.org/10.1016/j.tre.2018.06.001; Morales Chavez, M. M., Sarache, W., Costa, Y., & Soto, J. (2020). Multiobjective stochastic scheduling of upstream operations in a sustainable sugarcane supply chain. Journal of Cleaner Production, 276, 123305. https://doi.org/10.1016/j.jclepro.2020.123305; Morales-Chávez, M. M., Soto-Mejía, J. A., & Sarache, W. A. (2016). A mixed-integer linear programming model for harvesting, loading and transporting sugarcane. A case study in Peru. DYNA, 83(195), 173-179. https://doi.org/10.15446/dyna.v83n195.49490; Mota, B., Gomes, M. I., Carvalho, A., & Barbosa-Povoa, A. P. (2015). Towards supply chain sustainability: Economic, environmental and social design and planning. Journal of Cleaner Production, 105, 14-27. https://doi.org/10.1016/j.jclepro.2014.07.052; Muchow, R. C., Higgins, A. J., Rudd, A. V., & Ford, A. W. (1998). Optimising harvest date in sugar production: A case study for the Mossman mill region in Australia: II. Sensitivity to crop age and crop class distribution. Field Crops Research, 57(3), 243-251.; Mutenurea, M., Čučekb, L., Isafiade, A. J., & Kravanjab, Z. (2016). Synthesis of South Africa’s Biomass to Bioethanol Supply Network. CHEMICAL ENGINEERING, 52.; Mutran, V. M., Ribeiro, C. O., Nascimento, C. A. O., & Chachuat, B. (2020). Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry. Applied Energy, 258, 113978. https://doi.org/10.1016/j.apenergy.2019.113978; Oliveira, J. B., Lima, R. S., & Montevechi, J. A. B. (2016). Perspectives and relationships in Supply Chain Simulation: A systematic literature review. Simulation Modelling Practice and Theory, 62, 166-191. https://doi.org/10.1016/j.simpat.2016.02.001; Ometto, A. R., Hauschild, M. Z., & Roma, W. N. L. (2009). Lifecycle assessment of fuel ethanol from sugarcane in Brazil. Int J Life Cycle Assess, 12.; Osaki, M. R., & Seleghim Jr, P. (2017). Bioethanol and power from integrated second generation biomass: A Monte Carlo simulation. Energy Conversion and Management, 141, 274-284.; Osmani, A., & Zhang, J. (2013). Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties. Energy, 59, 157-172. https://doi.org/10.1016/j.energy.2013.07.043; Paiva, R. P. O., & Morabito, R. (2009). An optimization model for the aggregate production planning of a Brazilian sugar and ethanol milling company. Annals of Operations Research, 169(1), 117-130. https://doi.org/10.1007/s10479-008-0428-9; Pashangpour, R., Faghihi, F., & Soleymani, S. (2018). Optimized scheduling for electric lift trucks in a sugarcane agro-industry based on thermal, biomass and solar resources. International Journal of Environmental Science and Technology, 15(11), 2349-2358.; Pathumnakul S., & Nakrachata-Amon T. (2015). The Applications of Operations Research in Harvest Planning: A Case Study of the Sugarcane Industry in Thailand. Journal of Japan Industrial Management Association, 65(4E), 328-333. https://doi.org/10.11221/jima.65.328; Pelletier, N., Ustaoglu, E., Benoit, C., Norris, G., Rosenbaum, E., Vasta, A., & Sala, S. (2018). Social sustainability in trade and development policy. The International Journal of Life Cycle Assessment, 23(3), 629-639. https://doi.org/10.1007/s11367-016-1059-z; Pereira, R. D., Badino, A. C., & Cruz, A. J. (2020). Framework Based on Artificial Intelligence to Increase Industrial Bioethanol Production. Energy & Fuels, 34(4), 4670-4677.; Piewthongngam, K., Pathumnakul, S., & Setthanan, K. (2009). Application of crop growth simulation and mathematical modeling to supply chain management in the Thai sugar industry. Agricultural Systems, 102(1-3), 58-66. https://doi.org/10.1016/j.agsy.2009.07.002; Ramirez, C. A. M. (2017). Asocaña. Sector Agroindustrial de la Caña. https://www.asocana.org/; Ramirez, C. A. M. (2021a). Balance azucarero colombiano Asocaña 2000—2020 (toneladas). Asocaña - Sector Agroindustrial de la Caña. http://www.asocana.org/modules/documentos/5528.aspx; Ramirez, C. A. M. (2021b). Informe anual 2019—2020. Asocaña - Sector Agroindustrial de la Caña. http://www.asocana.org/modules/documentos/15398.aspx; Rojas, L. S. B. (2011). OPORTUNIDADES Y AMENAZAS DE LOS BIOCOMBUSTIBLES EN COLOMBIA [PONTIFICIA UNIVERSIDAD JAVERIANA]. https://repository.javeriana.edu.co/bitstream/handle/10554/12377/BuenoRojasLucySikint2011.pdf?sequence=1; UPME. (2018). BOLETÍN ESTADÍSTICO DE MINAS Y ENERGÍA 2016—2018. Unidad de Planeación Minero Energética, UPME. Bogotá. https://www1.upme.gov.co/PromocionSector/SeccionesInteres/Documents/Boletines/Boletin_Estadistico_2018.pdf; Pitakaso, R., & Sethanan, K. (2019). Adaptive large neighborhood search for scheduling sugarcane inbound logistics equipment and machinery under a sharing infield resource system. Computers and Electronics in Agriculture, 158, 313-325. https://doi.org/10.1016/j.compag.2019.02.001; Plà, L. M., Sandars, D. L., & Higgins, A. J. (2014). A perspective on operational research prospects for agriculture. Journal of the Operational Research Society, 65(7), 1078-1089. https://doi.org/10.1057/jors.2013.45; Polo, A., Peña, N., Muñoz, D., Cañón, A., & Escobar, J. W. (2018). Robust design of a closed-loop supply chain under uncertainty conditions integrating financial criteria. Omega. https://doi.org/10.1016/j.omega.2018.09.003; Poltroniere, S. C., Aliano Filho, A., Caversan, A. S., Balbo, A. R., & Florentino, H. de O. (2021). Integrated planning for planting and harvesting sugarcane and energy-cane for the production of sucrose and energy. Computers and Electronics in Agriculture, 184, 105956. https://doi.org/10.1016/j.compag.2020.105956; Prasara-A, J., & Gheewala, S. H. (2016). Sustainability of sugarcane cultivation: Case study of selected sites in north-eastern Thailand. Journal of Cleaner Production, 134, 613-622. https://doi.org/10.1016/j.jclepro.2015.09.029; Procaña. (2018). Colombian sugarcane Industry: Description. http://www.procana.org/new/quienes-somos/presentacion-del-sector.html; Qureshi, M. E., Qureshi, S. E., Bajracharya, K., & Kirby, M. (2008). Integrated Biophysical and Economic ModellingFramework to Assess Impacts of Alternative Groundwater Management Options. Water Resources Management, 22(3), 321-341. https://doi.org/10.1007/s11269-007-9164-1; Qureshi, M. E., Qureshi, S. E., & Wegener, M. K. (2007). Economic implications of alternative mill mud management options in the Australian sugar industry. Agricultural Economics, 36(1), 113-122.; Ramezani, M., Kimiagari, A. M., & Karimi, B. (2014). Closed-loop supply chain network design: A financial approach. Applied Mathematical Modelling, 38(15-16), 4099-4119. https://doi.org/10.1016/j.apm.2014.02.004; Rebitzer, G., Ekvall, T., Frischknecht, R., Hunkeler, D., Norris, G., Rydberg, T., Schmidt, W.-P., Suh, S., Weidema, B. P., & Pennington, D. W. (2004). Life cycle assessment. Part 1: Framework, goal and scope definition, inventory analysis, and applications. Environment International, 30(5), 701-720. https://doi.org/10.1016/j.envint.2003.11.005; Renouf, M. A., Wegener, M. K., & Pagan, R. J. (2010). Life cycle assessment of Australian sugarcane production with a focus on sugarcane growing. The International Journal of Life Cycle Assessment, 15(9), 927-937. https://doi.org/10.1007/s11367-010-0226-x; Reynolds, C., Buckley, J., Weinstein, P., & Boland, J. (2014). Are the Dietary Guidelines for Meat, Fat, Fruit and Vegetable Consumption Appropriate for Environmental Sustainability? A Review of the Literature. Nutrients, 6(6), 2251-2265. https://doi.org/10.3390/nu6062251; Rivera-Cadavid, L., Manyoma-Velásquez, P. C., & Manotas-Duque, D. F. (2019). Supply Chain Optimization for Energy Cogeneration Using Sugarcane Crop Residues (SCR). Sustainability, 11(23), 6565.; Rosa, W. (Ed.). (2017). Transforming Our World: The 2030 Agenda for Sustainable Development. En A New Era in Global Health. Springer Publishing Company. https://doi.org/10.1891/9780826190123.ap02; Ross, S. M. (2014). Introduction to probability models. Academic press.; Rota, C., Pugliese, P., Hashem, S., & Zanasi, C. (2018). Assessing the level of collaboration in the Egyptian organic and fair trade cotton chain. Journal of Cleaner Production, 170, 1665-1676. https://doi.org/10.1016/j.jclepro.2016.10.011; Sahebi, H., Nickel, S., & Ashayeri, J. (2014). Strategic and tactical mathematical programming models within the crude oil supply chain context—A review. Computers & Chemical Engineering, 68, 56-77. https://doi.org/10.1016/j.compchemeng.2014.05.008; Santibañez-Aguilar, J. E., González-Campos, J. B., Ponce-Ortega, J. M., Serna-González, M., & El-Halwagi, M. M. (2014). Optimal planning and site selection for distributed multiproduct biorefineries involving economic, environmental and social objectives. Journal of Cleaner Production, 65, 270-294. https://doi.org/10.1016/j.jclepro.2013.08.004; Santoro, E., Soler, E. M., & Cherri, A. C. (2017). Route optimization in mechanized sugarcane harvesting. Computers and Electronics in Agriculture, 141, 140-146. https://doi.org/10.1016/j.compag.2017.07.013; Saranwong, S., & Likasiri, C. (2017). Bi-level programming model for solving distribution center problem: A case study in Northern Thailand’s sugarcane management. Computers & Industrial Engineering, 103, 26-39. https://doi.org/10.1016/j.cie.2016.10.031; Sarkar, B., Mridha, B., Pareek, S., Sarkar, M., & Thangavelu, L. (2021). A flexible biofuel and bioenergy production system with transportation disruption under a sustainable supply chain network. Journal of Cleaner Production, 317, 128079. https://doi.org/10.1016/j.jclepro.2021.128079; Sartori, M. M. P., de Oliveira Florentino, H., Basta, C., & Leão, A. L. (2001). Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy. Energy, 26(11), 1031-1040.; Scully, M. J., Norris, G. A., Alarcon Falconi, T. M., & MacIntosh, D. L. (2021). Carbon intensity of corn ethanol in the United States: State of the science. Environmental Research Letters, 16(4), 043001. https://doi.org/10.1088/1748-9326/abde08; Semboloni, F. (2006). The CityDev Project: An Interactive Multi-agent Urban Model on the Web. En J. Portugali (Ed.), Complex Artificial Environments (pp. 155-163). Springer-Verlag. https://doi.org/10.1007/3-540-29710-3_10; Semenzato, R. (1995). A simulation study of sugar cane harvesting. Agricultural Systems, 47(4), 427-437. https://doi.org/10.1016/0308-521X(95)92108-I; Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. https://doi.org/10.1016/j.jclepro.2008.04.020; Shafie, S. M., Othman, Z., & Hami, N. (2020). Optimum location of biomass waste residue power plant in northern region: Economic and environmental assessment. International Journal of Energy Economics and Policy, 10(1), 150.; Shapiro, A. (2003). Monte Carlo Sampling Methods. En Handbooks in Operations Research and Management Science (Vol. 10, pp. 353-425). Elsevier. https://doi.org/10.1016/S0927-0507(03)10006-0; Shukla, M., & Jharkharia, S. (2013). Agri‐fresh produce supply chain management: A state‐of‐the‐art literature review. International Journal of Operations & Production Management, 33(2), 114-158. https://doi.org/10.1108/01443571311295608; Sihombing, L., Latief, Y., Rarasati, A. D., & Wibowo, A. (2018). Utilizing uncertainty management to analyze the uncertainty of toll road land acquisition. International Journal of Civil Engineering and Technology, 9(6), 1221-1228. Scopus.; Simchi-Levi, D., Chen, X., & Bramel, J. (2005). The logic of logistics. Theory, Algorithms, and Applications for Logistics and Supply Chain Management.; Sørensen, C. G., & Bochtis, D. D. (2010). Conceptual model of fleet management in agriculture. Biosystems Engineering, 105(1), 41-50. https://doi.org/10.1016/j.biosystemseng.2009.09.009; Soto-Silva, W. E., González-Araya, M. C., Oliva-Fernández, M. A., & Plà-Aragonés, L. M. (2017). Optimizing fresh food logistics for processing: Application for a large Chilean apple supply chain. Computers and Electronics in Agriculture, 136, 42-57. https://doi.org/10.1016/j.compag.2017.02.020; Soto-Silva, W. E., Nadal-Roig, E., González-Araya, M. C., & Pla-Aragones, L. M. (2016). Operational research models applied to the fresh fruit supply chain. European Journal of Operational Research, 251(2), 345-355. https://doi.org/10.1016/j.ejor.2015.08.046; Sowlati, T. (2016). Modeling of forest and wood residues supply chains for bioenergy and biofuel production. En Biomass Supply Chains for Bioenergy and Biorefining (pp. 167-190). Elsevier. https://doi.org/10.1016/B978-1-78242-366-9.00008-3; Soysal, M., Bloemhof-Ruwaard, J. M., Meuwissen, M. P., & van der Vorst, J. G. (2012). A review on quantitative models for sustainable food logistics management. International Journal on Food System Dynamics, 3(2), 136-155.; Standfield, L., Comans, T., & Scuffham, P. (2014). Markov modeling and discrete event simulation in health care: A systematic comparison. International Journal of Technology Assessment in Health Care, 30(2), 165-172. https://doi.org/10.1017/S0266462314000117; Stray, B. J., van Vuuren, J. H., & Bezuidenhout, C. N. (2012). An optimisation-based seasonal sugarcane harvest scheduling decision support system for commercial growers in South Africa. Computers and Electronics in Agriculture, 83, 21-31. https://doi.org/10.1016/j.compag.2012.01.009; Sun, F., Aguayo, M. M., Ramachandran, R., & Sarin, S. C. (2018). Biomass feedstock supply chain design–a taxonomic review and a decomposition-based methodology. International Journal of Production Research, 56(17), 5626-5659.; Sun, O., & Fan, N. (2020). A Review on Optimization Methods for Biomass Supply Chain: Models and Algorithms, Sustainable Issues, and Challenges and Opportunities. Process Integration and Optimization for Sustainability. https://doi.org/10.1007/s41660-020-00108-9; Teixeira, E. dos S., Rangel, S., Florentino, H. de O., & de Araujo, S. A. (2021). A review of mathematical optimization models applied to the sugarcane supply chain. International Transactions in Operational Research.; Tsolakis, N. K., Keramydas, C. A., Toka, A. K., Aidonis, D. A., & Iakovou, E. T. (2014). Agrifood supply chain management: A comprehensive hierarchical decision-making framework and a critical taxonomy. Biosystems Engineering, 120, 47-64. https://doi.org/10.1016/j.biosystemseng.2013.10.014; UN. (2017). United Nations sustainable development agenda. United Nations Sustainable Development. http://www.un.org/sustainabledevelopment/development-agenda/; Valin, H., Sands, R. D., van der Mensbrugghe, D., Nelson, G. C., Ahammad, H., Blanc, E., Bodirsky, B., Fujimori, S., Hasegawa, T., Havlik, P., Heyhoe, E., Kyle, P., Mason-D’Croz, D., Paltsev, S., Rolinski, S., Tabeau, A., van Meijl, H., von Lampe, M., & Willenbockel, D. (2014). The future of food demand: Understanding differences in global economic models. Agricultural Economics, 45(1), 51-67. https://doi.org/10.1111/agec.12089; van den Wall Bake, J. D., Junginger, M., Faaij, A., Poot, T., & Walter, A. (2009). Explaining the experience curve: Cost reductions of Brazilian ethanol from sugarcane. Biomass and Bioenergy, 33(4), 644-658. https://doi.org/10.1016/j.biombioe.2008.10.006; van Eijck, J., Batidzirai, B., & Faaij, A. (2014). Current and future economic performance of first and second generation biofuels in developing countries. Applied Energy, 135, 115-141. https://doi.org/10.1016/j.apenergy.2014.08.015; Verweij, B., Ahmed, S., Kleywegt, A. J., Nemhauser, G., & Shapiro, A. (2003). The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study. Computational Optimization and Applications, 24(2), 289-333. https://doi.org/10.1023/A:1021814225969; Will M. Bertrand, J., & Fransoo, J. C. (2002). Operations management research methodologies using quantitative modeling. International Journal of Operations & Production Management, 22(2), 241-264.; Wu, D., Baron, O., & Berman, O. (2009). Bargaining in competing supply chains with uncertainty. European Journal of Operational Research, 197(2), 548-556.; Yue, D., & You, F. (2014). Game-theoretic modeling and optimization of multi-echelon supply chain design and operation under Stackelberg game and market equilibrium. Computers & Chemical Engineering, 71, 347-361. https://doi.org/10.1016/j.compchemeng.2014.08.010; Yue, D., You, F., & Snyder, S. W. (2014). Biomass-to-bioenergy and biofuel supply chain optimization: Overview, key issues and challenges. Computers & Chemical Engineering, 66, 36-56. https://doi.org/10.1016/j.compchemeng.2013.11.016; Zahraee, S. M. (2020). Biomass supply chain environmental and socio-economic analysis: 40-Years comprehensive review of methods, decision issues, sustainability challenges, and the way forward. Biomass and Bioenergy, 33.; Zandi Atashbar, N., Labadie, N., & Prins, C. (2018). Modelling and optimisation of biomass supply chains: A review. International Journal of Production Research, 56(10), 3482-3506. https://doi.org/10.1080/00207543.2017.1343506; Zheng, X.-X., Liu, Z., Li, K. W., Huang, J., & Chen, J. (2019). Cooperative game approaches to coordinating a three-echelon closed-loop supply chain with fairness concerns. International Journal of Production Economics, 212, 92-110. https://doi.org/10.1016/j.ijpe.2019.01.011; Ziolkowska, J. R. (2020). Biofuels technologies: An overview of feedstocks, processes, and technologies. En Biofuels for a More Sustainable Future (pp. 1-19). Elsevier. https://doi.org/10.1016/B978-0-12-815581-3.00001-4; https://repositorio.unal.edu.co/handle/unal/82239; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

  5. 5

    Zdroj: Ingeniería; Vol. 20 No. 1 (2015): January - June; 129-138 ; Ingeniería; Vol. 20 Núm. 1 (2015): Enero - Junio; 129-138 ; 2344-8393 ; 0121-750X

    Popis súboru: application/pdf; text/html

    Relation: https://revistas.udistrital.edu.co/index.php/reving/article/view/8198/10153; https://revistas.udistrital.edu.co/index.php/reving/article/view/8198/10316; R. E. Bellman and Lofti A. Zadeh. Decision-making in a fuzzy environment. Management Science, 17(1):141– 164, 1970. [2] Juan Carlos Figueroa-García. An approximation method for type reduction of an interval Type-2 fuzzy set based on α-cuts. In IEEE, editor, Proceedings of FEDCSIS 2012, pages 1–6. IEEE, 2012. [3] Juan Carlos Figueroa-García. A general model for linear programming with interval type-2 fuzzy technological coefficients. In 2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS), pages 1–6. IEEE, 2012. [4] Juan Carlos Figueroa-García, Yurilev Chalco-Cano, and Heriberto Roma ́n-Flores. Distance measures for in- terval type-2 fuzzy numbers. Discrete Applied Mathematics, To appear(1), 2015. [5] Rafail N. Gasimov and Kursat Yenilmez. Solving fuzzy linear programming problems with linear membership functions. Turk J Math, 26(2):375–396, 2002. [6] George J. Klir and Tina A. Folger. Fuzzy Sets, Uncertainty and Information. Prentice Hall, 1992. [7] George J. Klir and Bo Yuan. Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall, 1995. [8] Jerry Mendel. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions. Prentice Hall, 1994. [9] Jerry M. Mendel, Robert I. John, and Feilong Liu. Interval type-2 fuzzy logic systems made simple. IEEE Transactions on Fuzzy Systems, 14(6):808–821, 2006. [10] Jaroslav Ramík. Soft computing: overview and recent developments in fuzzy optimization. Technical report, Institute for Research and Applications of Fuzzy Modeling, 2001. [11] Jaroslav Ramík. Optimal solutions in optimization problem with objective function depending on fuzzy pa- rameters. Fuzzy Sets and Systems, 158(17):1873–1881, 2007. [12] Jaroslav Ramík and Josef Rimánek. Inequality relation between fuzzy numbers and its use in fuzzy optimiza- tion. Fuzzy Sets and Systems, 16:123–138, 1985. [13] Heinrich Rommelfanger. FULPAL - An interactive method for solving multiobjective fuzzy linear programming problems, pages 279–299. Reidel, Dordrecht, 1990. [14] Heinrich Rommelfanger. FULP - A PC-supported procedure for solving multicriteria linear programming problems with fuzzy data, pages 154–167. Springer-Verlag, 1991. [15] Heinrich Rommelfanger. Entscheiden bei UnschSrfe - Fuzzy Decision Support-Systeme 2nd ed. Springer-Verlag, Berlin/Heidelberg, 1994. [16] Heinrich Rommelfanger. A general concept for solving linear multicriteria programming problems with crisp, fuzzy or stochastic values. Fuzzy Sets and Systems, 158(17):1892–1904, 2007.; https://revistas.udistrital.edu.co/index.php/reving/article/view/8198

  6. 6

    Popis súboru: xxxiv, 250 páginas; application/pdf

    Relation: J. C. Serrato, “Diseño computacional de agentes de extracción para la separación de compuestos orgánicos en corrientes acuosas. Aplicación al ácido láctico.”, Universidad Nacional de Colombia - Sede Bogotá, 2009. doi:10.7202/1016404ar.; K. A. Rodríguez, “Inclusion of toxicity and market availability in a Computer-Aided Molecular Design methodology”, 2019.; K. Rodríguez, “Computer Aided Molecular Design : State-of-the-art and environmen- tally friendly product design”, p. 9, 2019.; E. Stefanies, L. Constantinou, y C. Panayiotou, “A group-contribution method for predicting pure component properties of biochemical and safety interest”, Ind Eng Chem Res, vol. 43, núm. 19, pp. 6253–6261, 2004, doi:10.1021/ie0497184.; M. R. Eden, S. B. Jørgensen, R. Gani, y M. M. El-Halwagi, “A novel framework for simultaneous separation process and product design”, Chemical Engineering and Processing: Process Intensification, vol. 43, núm. 5, pp. 595–608, 2004, doi:10.1016/j.cep.2003.03.002.; J. Marrero y R. Gani, “Group-contribution based estimation of pure component properties”, Fluid Phase Equilib, vol. 183–184, pp. 183–208, 2001, doi:10.1016/S0378-3812(01)00431-9.; J. Rydberg, M. Cox, C. Musikas, y G. R. Choppin, Solvent Extraction Principles and Practice, vol. 2004.; A. Tejada, R. M. Montesinos, y R. Guzmán, Bioseparaciones. 2014.; M. L. van Delden, N. J. M. Kuipers, y A. B. de Haan, “Selection and evaluation of alternative solvents for caprolactam extraction”, Sep Purif Technol, vol. 51, núm. 2, pp. 219–231, 2006, doi:10.1016/j.seppur.2006.02.003.; G. W. Meindersma, A. Podt, y A. B. De Haan, “Selection of ionic liquids for the extraction of aromatic hydrocarbons from aromatic/aliphatic mixtures”, Fuel Processing Technology, vol. 87, núm. 1, pp. 59–70, 2005, doi:10.1016/j.fuproc.2005.06.002.; K. C. Sole, “Solvent extraction in the hydrometallurgical processing and purification of metals : process design and selected applications”, en Solvent Extraction and Liquid Membranes: Fundamentals and Applications in New Materials, 2018, pp. 141–200.; N. Tik, E. Bayraktar, y U. Mehmetoglu, “In situ reactive extraction of lactic acid from fermentation media”, Journal of Chemical Technology and Biotechnology, vol. 76, núm. 7, pp. 764–768, 2001, doi:10.1002/jctb.449.; A. B. de Haan, “Affinity solvents for intensified organics extraction: Development challenges and prospects”, Tsinghua Sci Technol, vol. 11, núm. 2, pp. 171–180, 2006, doi:10.1016/S1007-0214(06)70172-9.; W. L. McCabe, J. C. Smith, y P. Harriott, Operaciones unitarias en Ingeniería Química. 1991.; J. Gmehling, M. Kleiber, B. Kolbe, y J. Rarey, Chemical Thermodynamics for Process Simulation. 2019. doi:10.1002/9783527809479.; J. M. Smith, H. C. van Ness, y M. M. Abott, Introducción a la Termodinámica en Ingeniería Química. 2007. [En línea]. Disponible en: http://librosysolucionarios.net/; R. E. Treybal, “Azeotropes”, A-to-Z Guide to Thermodynamics, Heat and Mass Transfer, and Fluids Engineering, 2008, doi:10.1615/atoz.a.azeotropes.; M. C. M. Cockrem, E. N. Lightfoot, y J. H. Flatt, “Solvent Selection for Extraction from Dilute Solution”, Sep Sci Technol, vol. 24, núm. 11, pp. 769–807, 1989, doi:10.1080/01496398908049876.; J. Medina-Mora, “Optimización Multiobjetivo para la selección de solventes, aplicable a la Extracción Líquido-Líquido”, 2010.; E. Brignole y S. Pereda, Phase equilibrium engineering principles, vol. 3. 2013. doi:10.1016/B978-0-444-56364-4.00006-6.; L. E. K. Achenie, R. Gani, y V. Venkatasubramanian, Computer Aided Molecular Design: Theory and Practice. 2003.; N. G. Martín, Mariano Eden, Mario R. Chemmangattuvalappil, Tools for Chemical Product Design. 2017.; H. Fruehbeis, R. Klein, y H. Wallmeier, “Computer-Assisted Molecular Design (CAMD) - An Overview”, ChemInform, vol. 18, núm. 35, pp. 403–418, 1987, doi:10.1002/chin.198735397.; L. A. Cisternas y E. D. Gálvez, “Principles for chemical products design”, Computer Aided Chemical Engineering, vol. 21, núm. C, pp. 1107–1112, 2006, doi:10.1016/S1570-7946(06)80194-X.; G. D. Moggridge y E. L. Cussler, “An introduction to chemical product design”, Chemical Engineering Research and Design, vol. 78, núm. 1, pp. 5–11, 2000, doi:10.1205/026387600527022.; A. K. Tula, D. K. Babi, J. Bottlaender, M. R. Eden, y R. Gani, “A computer-aided software-tool for sustainable process synthesis-intensification”, Comput Chem Eng, vol. 105, pp. 74–95, 2017, doi:10.1016/j.compchemeng.2017.01.001.; L. Y. Ng, N. G. Chemmangattuvalappil, V. A. Dev, y M. R. Eden, Mathematical Principles of Chemical Product Design and Strategies, vol. 39. 2016. doi:10.1016/B978-0-444-63683-6.00001-0.; R. Gani, “Chemical product design: Challenges and opportunities”, Comput Chem Eng, vol. 28, núm. 12, pp. 2441–2457, 2004, doi:10.1016/j.compchemeng.2004.08.010.; L. Y. Ng, F. K. Chong, y N. G. Chemmangattuvalappil, “Challenges and opportunities in computer-aided molecular design”, Comput Chem Eng, vol. 81, pp. 115–129, 2015, doi:10.1016/j.compchemeng.2015.03.009.; S. S. Y. Wong, W. Luo, y K. C. C. Chan, “EvoMD: An algorithm for evolutionary molecular design”, IEEE/ACM Trans Comput Biol Bioinform, vol. 8, núm. 4, pp. 987–1003, 2011, doi:10.1109/TCBB.2010.100.; J. Scheffczyk, L. Fleitmann, A. Schwarz, M. Lampe, A. Bardow, y K. Leonhard, “COSMO-CAMD: A framework for optimization-based computer-aided molecular design using COSMO-RS”, Chem Eng Sci, vol. 159, pp. 84–92, 2017, doi:10.1016/j.ces.2016.05.038.; C. C. Solvason, “Integrated Multiscale Chemical Product Design using Property Clustering and Decomposition Techniques in a Reverse Problem Formulation”, 2011.; R. Gani, L. E. K. Achenie, y V. Venkatasubramanian, “Chapter 1: Introduction to CAMD”, en Computer Aided Molecular Design: Theory and Practice, 2003, pp. 3–21.; N. D. Austin, N. V. Sahinidis, y D. W. Trahan, “Computer-aided molecular design: An introduction and review of tools, applications, and solution techniques”, Chemical Engineering Research and Design, vol. 116, núm., pp. 2–26, 2016, doi:10.1016/j.cherd.2016.10.014.; M. Harini, J. Adhikari, y K. Y. Rani, “A review on property estimation methods and computational schemes for rational solvent design: A focus on pharmaceuticals”, Ind Eng Chem Res, vol. 52, núm. 21, pp. 6869–6893, 2013, doi:10.1021/ie301329y.; P. M. Harper, R. Gani, P. Kolar, y T. Ishikawa, “Computer-aided molecular design with combined molecular modeling and group contribution”, Fluid Phase Equilib, vol. 158–160, pp. 337–347, 1999, doi:10.1016/s0378-3812(99)00089-8.; T. Martin, User’s guide for T.E.S.T. (version 4.2) (Toxicity Estimation Software Tool) A program to estimate toxicity from molecular structure. 2016, p. 63.; J. Song y H. H. Song, “Computer-aided molecular design of environmentally friendly solvents for separation processes”, Chem Eng Technol, vol. 31, núm. 2, pp. 177–187, 2008, doi:10.1002/ceat.200700233.; J. Y. Ten, M. H. Hassim, D. K. S. Ng, y N. G. Chemmangattuvalappil, “The Incorporation of Safety and Health Aspects as Design Criteria in a Novel Chemical Product Design Framework”, Computer Aided Chemical Engineering, vol. 39, pp. 197–220, 2016, doi:10.1016/B978-0-444-63683-6.00007-1.; R. Gani, B. Nielsen, y A. Fredenslund, “A group contribution approach to computer‐aided molecular design”, AIChE Journal, vol. 37, núm. 9, pp. 1318–1332, 1991, doi:10.1002/aic.690370905.; O. Odele y S. Macchietto, “Computer Aided Molecular Design: A Novel Method for Optimal Solvent Selection”, Fluid Phase Equilib, vol. 00226020, núm. 3, pp. 47–54, 1993.; P. M. Harper y R. Gani, “A multi-step and multi-level approach for computer aided molecular design”, Comput Chem Eng, vol. 24, núm. 2–7, pp. 677–683, 2000, doi:10.1016/S0098-1354(00)00410-5.; B. C. Roughton, “Development of Computer-Aided Molecular Design Methods for Bioengineering Applications”, 2013.; S. Cignitti, I. Rodriguez-Donis, J. Abildskov, X. You, N. Shcherbakova, y V. Gerbaud, “CAMD for entrainer screening of extractive distillation process based on new thermodynamic criteria”, Chemical Engineering Research and Design, vol. 147, pp. 721–733, 2019, doi:10.1016/j.cherd.2019.04.038.; B. van Dyk y I. Nieuwoudt, “Design of solvents for extractive distillation”, Ind Eng Chem Res, vol. 39, núm. 5, pp. 1423–1429, 2000, doi:10.1021/ie9904753.; N. Medina-Herrera, I. E. Grossmann, M. S. Mannan, y A. Jiménez-Gutiérrez, “An approach for solvent selection in extractive distillation systems including safety considerations”, Ind Eng Chem Res, vol. 53, núm. 30, pp. 12023–12031, 2014, doi:10.1021/ie501205j.; S. Kossack, K. Kraemer, R. Gani, y W. Marquardt, “A systematic synthesis framework for extractive distillation processes”, Chemical Engineering Research and Design, vol. 86, núm. 7, pp. 781–792, 2008, doi:10.1016/j.cherd.2008.01.008.; T. Zhou, Z. Song, X. Zhang, R. Gani, y K. Sundmacher, “Optimal Solvent Design for Extractive Distillation Processes: A Multiobjective Optimization-Based Hierarchical Framework”, Ind Eng Chem Res, vol. 58, núm. 15, pp. 5777–5786, 2019, doi:10.1021/acs.iecr.8b04245.; J. Sun, H. Zhang, A. Zhou, Q. Zhang, y K. Zhang, “A new learning-based adaptive multi-objective evolutionary algorithm”, Swarm Evol Comput, vol. 44, núm. December 2017, pp. 304–319, 2019, doi:10.1016/j.swevo.2018.04.009.; A. T. Karunanithi, C. Acquah, L. E. K. Achenie, S. Sithambaram, y S. L. Suib, “Solvent design for crystallization of carboxylic acids”, Comput Chem Eng, vol. 33, núm. 5, pp. 1014–1021, 2009, doi:10.1016/j.compchemeng.2008.11.003.; V. Venkatasubramanian, K. Chan, y J. M. Caruthers, “Evolutionary Design of Molecules with Desired Properties Using the Genetic Algorithm”, J Chem Inf Comput Sci, vol. 35, núm. 2, pp. 188–195, 1995, doi:10.1021/ci00024a003.; M. Mattei, M. Hill, G. M. Kontogeorgis, y R. Gani, “Design of an emulsion-based personal detergent through a model-based chemical product design methodology”, Computer Aided Chemical Engineering, vol. 32, pp. 817–822, 2013, doi:10.1016/B978-0-444-63234-0.50137-8.; R. Gani, “Chapter 14 Case studies in chemical product design - use of CAMD techniques”, Computer Aided Chemical Engineering, vol. 23, núm. 1991, pp. 435–458, 2007, doi:10.1016/S1570-7946(07)80017-4.; K. Zhou Teng; Wang, Jiayuan; Mcbride, Kevin; Sundmacher, “Optimal Design of Solvents for Extractive Reaction Process”, AICHE Journal, vol. 61, núm. 3, pp. 857–866, 2015, doi:10.1002/aic.; M. Skiborowski, “Process synthesis and design methods for process intensification”, Curr Opin Chem Eng, vol. 22, pp. 216–225, 2018, doi:10.1016/j.coche.2018.11.004.; S. J. Patel, “Integrating Safety Issues in Optimizing Solven Selection and Porcess Design”, 2010.; J. Ooi, D. K. S. Ng, y N. G. Chemmangattuvalappil, “A Systematic Molecular Design Framework with the Consideration of Competing Solvent Recovery Processes”, Ind Eng Chem Res, vol. 58, núm. 29, pp. 13210–13226, 2019, doi:10.1021/acs.iecr.9b01894.; J. E. Ourique y A. Silva Telles, “Computer-aided molecular design with simulated annealing and molecular graphs”, Comput Chem Eng, vol. 22, núm. SUPPL.1, pp. 0–3, 1998, doi:10.1016/s0098-1354(98)00108-2.; J. Heintz, J. P. Belaud, N. Pandya, M. Teles Dos Santos, y V. Gerbaud, “Computer aided product design tool for sustainable product development”, Comput Chem Eng, vol. 71, pp. 362–376, 2014, doi:10.1016/j.compchemeng.2014.09.009.; J. Heintz, “Systemic approach and decision process for sustainability in chemical engineering: Applcation to computer aided product design. PhD Thesis”, p. 256, 2012.; J. Y. Ten, M. H. Hassim, D. K. S. Ng, y N. G. Chemmangattuvalappil, “A molecular design methodology by the simultaneous optimisation of performance, safety and health aspects”, Chem Eng Sci, vol. 159, pp. 140–153, 2017, doi:10.1016/j.ces.2016.03.026.; J. Devillers, Genetic Algorithms in Molecular Modeling, vol., núm. June. 2016. doi:10.1016/b978-0-12-213810-2.x5000-2.; B. Lin, S. Chavali, K. Camarda, y D. C. Miller, “Computer-aided molecular design using Tabu search”, Comput Chem Eng, vol. 29, núm. 2, pp. 337–347, 2005, doi:10.1016/j.compchemeng.2004.10.008.; A. S. Hukkerikar, B. Sarup, A. Ten Kate, J. Abildskov, G. Sin, y R. Gani, “Group-contribution+ (GC+) based estimation of properties of pure components: Improved property estimation and uncertainty analysis”, Fluid Phase Equilib, vol. 321, pp. 25–43, 2012, doi:10.1016/j.fluid.2012.02.010.; A. S. Hukkerikar, S. Kalakul, B. Sarup, D. M. Young, G. Sin, y R. Gani, “Estimation of environment-related properties of chemicals for design of sustainable processes: Development of group-contribution+ (GC +) property models and uncertainty analysis”, J Chem Inf Model, vol. 52, núm. 11, pp. 2823–2839, 2012, doi:10.1021/ci300350r.; A. S. Hukkerikar, G. Sin, J. Abildskov, B. Sarup, y R. Gani, Development of pure component property models for chemical product-process design and analysis, núm. September. 2013.; R. L. Haupt y S. E. Haupt, Pratical Genetic Algotithms, vol. 2004.; R. Kumar, Optimization: Algorithms and Applications, vol. CRC Press, 2015.; Z. Dostál, Optimal Quadratic Programming Algorithms: With Applications to Variational Inequalities, vol. 23. 2009. doi:10.1007/b138610.; J. A. Snyman y D. N. Wilke, Practical Mathematical Optimization, vol. 133. Cham, Switzerland, 2005. doi:10.1007/b105200.; K.-H. Chang, “Chapter 3 - Design Optimization”, en Design Theory and Methods Using CAD/CAE, 2015, pp. 103–210. doi:10.1080/03772063.2020.1842159.; J. A. Caballero y I. E. Grossmann, “A review of the state of the art in optimization”, RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, vol. 4, núm. 1, pp. 5–23, 2007, doi:10.1016/s1697-7912(07)70188-7.; X.-S. Yang, Nature-Inspired Optimization Algorithms. 2020.; C. A. C. Coello, “Introduccion a la Computacion Evolutiva”, núm. 16, p. 310, 2004.; M. A. Iglesias-Solano y A. B. Iglesias-Carbonell, “La Computación Evolutiva y sus Paradigmas Paradigms of Evolutionary Computing”, Investigación y Desarrollo en TIC, vol. 2, pp. 29–38, 2011.; N. Yusup, A. M. Zain, y S. Z. M. Hashim, “Evolutionary techniques in optimizing machining parameters: Review and recent applications (2007-2011)”, Expert Syst Appl, vol. 39, núm. 10, pp. 9909–9927, 2012, doi:10.1016/j.eswa.2012.02.109.; A. Menon, Frontiers of Evolutionary Computation, vol., núm. 2004.; C. J. Correa-Villalón, “Diseño de un Algoritmo Evolutivo para atacar Problemas NP-Duros basado en la Técnica Transgénicas”, Universidad Autónoma de Aguascalientes (México), 2010. doi: -.; D. E. Goldberg, “Genetic Algorithms in Search Optimization & Machine Learning”. p. 432, 1989.; J. H. Holland, “Genetic Algorithms - Computer programs that ‘evolve’ in ways that resemble natural selection can solve complex problems even their creators do not fully understand”, Scientific American. pp. 66–72, 1992.; J. H. Holland, C. Langton, y S. W. Wilson, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence. 1992.; M. Pelikan, Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms, vol. 53, núm. 9. 2013. doi:10.1017/CBO9781107415324.004.; T. Bäck, “Evolutionary algorithms in theory and practice: Evolution strategies, evolutionary programming, genetic algorithms”. p. 315, 1996.; Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs, vol. 1, núm. 1996.; D. A. Coley, “An Introduction to Genetic Algorithms for Scientists and Engineers”. p. 185, 1999.; S. Kumar y P. J. Bentley, “Biologically Inspired Evolutionary Development”, ICES, vol., núm., pp. 57–68, 2003, doi:10.1007/3-540-36553-2_6.; D. Vasiljević, Classical and Evolutionary Algorithms in the Optimization of Optical Systems, vol., núm. 2006.; M. Melanie, An introduction to genetic algorithms, vol. 1999. doi:10.1016/S0898-1221(96)90227-8.; S. N. Sivanandam y S. N. Deepa, Introduction to Genetic Algorithms, vol. 2008.; D. Simon, Evolutionary Optimization Aglorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence, vol., núm. John Wiley & Sons, Inc., 2013.; W.-H. Steeb, The nonlinear workbook: Chaos, Fractals, Celular Automata, Neural Networks, Genetic Algorithms, Fuzzy Logic with C++, Java, SymbolicC++ and Reduce Programs, vol. 1999.; J. Branke, Evolutionary optimization in dynamic environment, vol. 2002. doi:10.1109/ICCP.2009.5284794.; C. B. Lucasius y G. Kateman, “Understanding and using genetic algorithms Part 2. Representation, configuration and hybridization”, Chemometrics and Intelligent Laboratory Systems, vol. 25, pp. 99–145, 1994.; F. Rothlauf, Representations for Genetic and Evolutionary Algorithms, vol. 2006.; F. Corno, M. Sonza Reorda, y G. Squillero, “VEGA: a verification tool based on genetic algorithms”, Proceedings - IEEE International Conference on Computer Design: VLSI in Computers and Processors, pp. 321–326, 1998, doi:10.1109/iccd.1998.727069.; N. Srinivas y K. Deb, “Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms”, núm. 0, 1386.; K. Deb, S. Agrawal, A. Pratap, y T. Meyarivan, “A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1917, pp. 849–858, 2000, doi:10.1007/3-540-45356-3_83.; T. Murata y H. Ishibuchi, “MOGA: multi-objective genetic algorithms”, Proceedings of the IEEE Conference on Evolutionary Computation, vol. 1, pp. 289–294, 1995, doi:10.1109/icec.1995.489161.; E. Zitzler y L. Thiele, “Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach”, vol. 3, núm. 4, pp. 257–271, 1999.; E. Zitzler, M. Laumanns, y L. Thiele, “SPEA2: Improving the Strength Pareto Evolutionary Algorithm”, TIK-Report 103 May, pp. 1–21, 2001, doi:10.1007/978-3-319-11119-3_4.; J. Gomez, “Self adaptation of operator rates in evolutionary algorithms”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3102, pp. 1162–1173, 2004, doi:10.1007/978-3-540-24854-5_113.; J. Gómez, “Hybrid Adaptive Evolutionary Algorithm Hyper Heuristic”, pp. 1–5, 2014.; C. R. Reeves y J. E. Rowe, Genetic algorithms: Principles and Perspectives - A Guide to GA Theory. 2002.; S. Bandyopadhyay y S. K. Pal, Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence, vol. 2007.; L. Chambers, Practical Handbook of Genetic Algorithms - New Frontiers Volume II. 1995.; D. B. Hibbert, “Genetic algorithms in Chemistry”, Chemometrics and Intelligent Laboratory Systems, vol. 19, núm. 8 SPEC., pp. 277–293, 1993, doi:10.1016/S0010-4485(03)00002-2.; L. Elliott, D. B. Ingham, A. G. Kyne, N. S. Mera, M. Pourkashanian, y C. W. Wilson, “Genetic algorithms for optimisation of chemical kinetics reaction mechanisms”, Progress in Enery and Combustion Science, vol. 30, pp. 297–328, 2004, doi:10.1016/j.pecs.2004.02.002.; C. B. Lucasius y G. Kateman, “Understanding and using genetic algorithms Part 1. Concepts, properties and context”, Chemometrics and Intelligent Laboratory Systems, vol. 19, núm. 1, pp. 1–33, 1993, doi:10.1016/0169-7439(93)80079-W.; L. Gosselin, M. Tye-Gingras, y F. Mathieu-Potvin, “Review of utilization of genetic algorithms in heat transfer problems”, Int J Heat Mass Transf, vol. 52, núm. 9–10, pp. 2169–2188, 2009, doi:10.1016/j.ijheatmasstransfer.2008.11.015.; J. G. Andreasen, U. Larsen, T. Knudsen, L. Pierobon, y F. Haglind, “Selection and optimization of pure and mixed working fluids for low grade heat utilization using organic rankine cycles”, Energy, vol. 73. pp. 204–213, 2014. doi:10.1016/j.energy.2014.06.012.; Z. Kravanja y M. Bogataj, “26 European Symposium on Computer Aided Process Engineering-Elsevier”, Computer Aided Chemical Engineering, vol. 38, p. 588, 2016.; M. Fan, J. Hu, R. Cao, W. Ruan, y X. Wei, “A review on experimental design for pollutants removal in water treatment with the aid of artificial intelligence”, Chemosphere, vol. 200, pp. 330–343, 2018, doi:10.1016/j.chemosphere.2018.02.111.; A. Maiocchi, “Genetic algorithms in molecular modelling: a review”, en Data Handling in Science and Technology, 2003, pp. 109–139. doi:10.1016/S0922-3487(03)23004-5.; T. Lisboa, “Multi-Objective Optimization”, Técnico Lisboa. pp. 148–173.; A. Ramos, “Optimización Multicriterio”, Universidad Pontificia Comillas, núm. p. 16.; C. A. C. Coello, “Aplicaciones de los Algoritmos Evolutivos Multiobjetivo”, núm. 2508, 2012.; H. Massam, “Multi-criteria (MCDM) Decision Making Techniques in Planning”, Prog Plann, vol. 30, núm. Mcdm, pp. 1–84, 1988.; P. L. Yu, “Multiple criteria decision making: Five basic concepts”, Handbooks in Operations Research and Management Science, vol. 1, núm. C, pp. 663–699, 1989, doi:10.1016/S0927-0507(89)01011-X.; C. A. C. Coello, G. B. Lamont, y D. A. Van Veldhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems, vol. 2007. doi:10.1080/00949659608811725.; S. Chand y M. Wagner, “Evolutionary many-objective optimization: A quick-start guide”, Surveys in Operations Research and Management Science, vol. 20, núm. 2, pp. 35–42, 2015, doi:10.1016/j.sorms.2015.08.001.; R. T. Marler y J. S. Arora, “Survey of multi-objective optimization methods for engineering”, Structural and Multidisciplinary Optimization, vol. 26, núm. 6, pp. 369–395, 2004, doi:10.1007/s00158-003-0368-6.; C. Zopounidis y P. M. Pardalos, Handbook of Multicriteria Analysis. 2010.; D. R. Insua, “Sobre soluciones optimas en problemas de optimizacion multiobjetivo”, Trabajos de Investigacion Operativa, vol. 2, núm. 1, pp. 49–67, 1987, doi:10.1007/BF02888810.; C. M. Subía, “Desarrollo de una Guía Metodologíca sobre Computación Evolutiva y Algoritmos Genéticos, para la Optimiziación Evolutiva Multiobjetivo”, 2014. doi:10.4324/9781315853178.; S. Hernández, “Del diseño convencional al diseño óptimo. Posibilidades y variantes”, Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, vol. 9, pp. 259–270, 1993.; H. Mukai, “Algorithms for Multicriterion Optimization”, IEEE Trans Automat Contr, vol. 25, núm. 2, pp. 177–186, 1980, doi:10.1109/TAC.1980.1102298.; G. Giorgi, B. Jiménez, y V. Novo, “Approximate Karush–Kuhn–Tucker Condition in Multiobjective Optimization”, J Optim Theory Appl, vol. 171, núm. 1, pp. 70–89, 2016, doi:10.1007/s10957-016-0986-y.; E. Mezura-Montes y C. A. Coello Coello, “Conceptos de Optimización Multiobjetivo para el Manejo de Restricciones en Algoritmos Evolutivos: Un Estudio Comparativo”, Proceedings of the 1st Mexican Conference on Evolutionary Computation (COMCEV 2003), pp. 1–12, 2003.; N. Riquelme, C. von Lücken, y B. Barán, “Performace metrics in multi-objective optimization”, en 2015 XLI Latin American Computing Conference (CLEI) Performance, 2015.; B. A. Cuartas Torres, “Metodología para la optimización de múltiples objetivos basada en ag y uso de preferencias”, Universidad Nacional de Colombia - Sede Medellín, 2009. [En línea]. Disponible en: http://www.bdigital.unal.edu.co/2237/%5Cnhttp://www.bdigital.unal.edu.co/2237/1/43908352.2009.pdf; N. Riquelme, C. Von Lücken, y B. Barán, “Performance metrics in multi-objective optimization”, Proceedings - 2015 41st Latin American Computing Conference, CLEI 2015, vol. 1, p. 11, 2015, doi:10.1109/CLEI.2015.7360024.; J. A. Párraga, “Clustering difuso multi-objetivo de genes basado en información biológica externa y datos de expresión génica”, Universidad de Santiago de Chile, 2017. doi:10.1088/1742-6596/134/1/012001.; J. C. Castro, “Modelo de optimización multiobjetivo para el algoritmo evolutivo HAEA (Hybrid Adaptative Evolutionary Algoritm)”, Universidad Nacional de Colombia, 2020.; K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, vol. John Wiley & Sons, 2001.; R. T. Marler y J. S. Arora, “The weighted sum method for multi-objective optimization: New insights”, Structural and Multidisciplinary Optimization, vol. 41, núm. 6, pp. 853–862, 2010, doi:10.1007/s00158-009-0460-7.; A. Singh y S. Kumar, “Multiple Objectives Mathematical Programming Using Payoff Techniques”, vol. 9, núm. 1, pp. 39–46, 2012.; S. Obayashi, D. Sasaki, y A. Oyama, “Finding tradeoffs by using multiobjective optimization algorithms”, Trans Jpn Soc Aeronaut Space Sci, vol. 47, núm. 155, pp. 51–58, 2004, doi:10.2322/tjsass.47.51.; M. Sakawa, Genetic algorithms and fuzzy multiobjective optimization, vol. 1, núm. 2002.; R. Wang, R. C. Purshouse, y P. J. Fleming, “Preference-inspired co-evolutionary algorithms using weight vectors”, Eur J Oper Res, vol. 243, núm. 2, pp. 423–441, 2015, doi:10.1016/j.ejor.2014.05.019.; W. Wang, S. Ying, L. Li, Z. Wang, y W. Li, “An improved decomposition-based multiobjective evolutionary algorithm with a better balance of convergence and diversity”, Applied Soft Computing Journal, vol. 57, pp. 627–641, 2017, doi:10.1016/j.asoc.2017.03.041.; Q. Zhang, W. Zhu, B. Liao, X. Chen, y L. Cai, “A modified PBI approach for multi-objective optimization with complex Pareto fronts”, Swarm Evol Comput, vol. 40, núm. February, pp. 216–237, 2018, doi:10.1016/j.swevo.2018.02.001.; C. A. C. Coello, “Introducción a la Optimización Evolutiva Multiobjetivo”, Apuntes de clase: Introducción a la optimización multiobjetivo., vol., núm. 4. pp. 1–144, 2012.; J. D. Schaffer, “Multiple objective optimization with vector evaluated genetic algorithms”, The 1st international Conference on Genetic Algorithms, núm. JANUARY 1985, pp. 93–100, 1985.; K. Deb, A. Pratap, S. Agarwal, y T. Meyarivan, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II”, IEEE Transactions on Evolutionary Computation, vol. 6, núm. 2, pp. 182–197, 2002, doi:10.1109/4235.996017.; C. A. Correa Flórez, R. Andrés Bolaños, y A. Molina Cabrera, “Algoritmo multiobjetivo NSGA-II aplicado al problema de la mochila.”, Scientia Et Technica, vol. 2, núm. 39, pp. 206–211, 2008.; L. Lopez, R. A. Hincapié, y R. A. Gallego, “Planeamiento multi-objetivo de sistemas de distribución usando un algoritmo evolutivo NSGA-II”, Revista Escuela de Ingeniería de Antioquía, vol. 15, núm. 15, pp. 141–151, 2011.; N. Dahmani, F. Clautiaux, S. Krichen, y E. G. Talbi, “Self-adaptive metaheuristics for solving a multi-objective 2-dimensional vector packing problem”, Applied Soft Computing Journal, vol. 16, pp. 124–136, 2014, doi:10.1016/j.asoc.2013.12.006.; L. Wang, A. H. C. Ng, y K. Deb, “Multi-objective Evolutionary Optimisation for Product Design and Manufacturing”, Assembly Automation, vol. 32, núm. 4, pp. 142–147, 2012, doi:10.1108/aa.2012.03332daa.009.; J. Gomez, “Self adaptation of operator rates for multimodal optimization”, Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004, vol. 2, pp. 1720–1726, 2004, doi:10.1109/cec.2004.1331103.; GECCO ’19, “MOHAEA: A Multi-objective Hybrid Adaptive Evolutionary Algorithm”, en GECCO ’19, July 13–17, 2019, 2019, pp. 1–3.; J. Horn, N. Nafpliotis, y D. E. Goldberg, “A niched Pareto genetic algorithm for multiobjective optimization”, en First IEEE Conference on Evolutionary Computation, 2002, pp. 82–87. doi:10.1109/icec.1994.350037.; C.-L. Hwang, Y.-J. Lai, y T.-Y. Liu, “A New Approach for Multiple Objective Decision Making”, Comput Oper Res, vol. 20, núm. 8, pp. 889–899, 1993.; J. G. Vlachogiannis y K. Y. Lee, “Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems”, Expert Syst Appl, vol. 36, núm. 8, pp. 10802–10808, 2009, doi:10.1016/j.eswa.2009.02.079.; L. C. Cagnina, “Optimización Mono y Multiobjetivo a través de una Heurística de Inteligencia Colectiva”, pp. 54–72, 2010.; A. Lara López, “Un estudio de las Estrategias Evolutivas para problemas Multiobjetivo.”, pp. 23–25, 2003.; N. A. Ramírez, “Una nueva propuesta para optimización multiobjetivo basada en búsqueda dispersa (Scatter Search)”, 2006.; M. Gul, E. Celik, N. Aydin, A. Taskin Gumus, y A. F. Guneri, “A state of the art literature review of VIKOR and its fuzzy extensions on applications”, Applied Soft Computing Journal, vol. 46, pp. 60–89, 2016, doi:10.1016/j.asoc.2016.04.040.; Y.-Z. Lu, Y.-W. Chen, M.-R. Chen, P. Chen, y G.-Q. Zeng, Extremal Optimization: Fundamentals, Algorithms, and Applications, vol. 2016.; S. S. Santander-Jiménez, M. A. Vega-Rodríguez, J. A. Gómez-Pulido, y J. M. Sánchez-Pérez, “Una adaptación multiobjetivo y paralela del algoritmo Artificial Bee Colony aplicada a la inferencia filogenética”, 1996.; C.-K. Goh y K. C. Tan, Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms, vol. 186. 2009. doi:10.1007/978-3-540-95976-2.; M. Macías Infantes, “Estudio Comparativo de Técnicas de Optimización para la Actualización de Modelos de Elementos Finitos”, 2016.; L. C. Jain y N. M. Martin, Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms: Industrial Applications, vol. 1. 1998.; G. Toscano, “Optimización Multiobjetivo usando un Micro Algoritmo Genético”, Universidad Veracurzana - LANIA, 2001.; C. Almeida, N. Amarilla, y B. Barán, “Optimización Multiobjetivo en la Planificación de Centrales Telefónicas”, 2003.; C. Castillo, “Aplicación de la Programacion Multiobjetivo en la Optimización del Tráfico Generado por un IDS/IPS”, Rev. Tecnol. - Journal of Technology, vol. 11, núm. 1, pp. 41–55, 2012.; S. Ruiz, O. D. Castrillón, y W. A. Sarache, “Una metodología multiobjetivo para optimizar un ambiente job shop”, Informacion Tecnologica, vol. 23, núm. 1, pp. 35–46, 2012, doi:10.4067/S0718-07642012000100005.; M. Guzek, J. E. Pecero, B. Dorronsoro, y P. Bouvry, “Multi-objective evolutionary algorithms for energy-aware scheduling on distributed computing systems”, Applied Soft Computing Journal, vol. 24, pp. 432–446, 2014, doi:10.1016/j.asoc.2014.07.010.; C. Carnevale, G. Finzi, E. Pisoni, y M. Volta, “Multi-objective analysis to control ozone exposure”, en Developments in Environmental Science, 2007, pp. 96–108. doi:10.1016/S1474-8177(07)06023-8.; P. S. Moura y A. T. de Almeida, “Multi-objective optimization of a mixed renewable system with demand-side management”, Renewable and Sustainable Energy Reviews, vol. 14, núm. 5, pp. 1461–1468, 2010, doi:10.1016/j.rser.2010.01.004.; M. J. Bastidas, R. F. Bermúdez, G. P. Jaramillo, y F. Chejne, “Optimización termoeconómica y ambiental usando algoritmos genéticos multiobjetivo”, Informacion Tecnologica, vol. 21, núm. 4, pp. 35–44, 2010, doi:10.1612/inf.tecnol.4384it.09.; P. J. Copado-Méndez, C. Pozo, G. Guillén-Gosálbez, y L. Jiménez, “Enhancing the ε-constraint method through the use of objective reduction and random sequences: Application to environmental problems”, Comput Chem Eng, vol. 87, pp. 36–48, 2016, doi:10.1016/j.compchemeng.2015.12.016.; M. N. Naz, M. I. Mushtaq, M. Naeem, M. Iqbal, M. W. Altaf, y M. Haneef, “Multicriteria decision making for resource management in renewable energy assisted microgrids”, Renewable and Sustainable Energy Reviews, vol. 71, núm. December 2016, pp. 323–341, 2017, doi:10.1016/j.rser.2016.12.059.; R. T. F. Ah. King, K. Deb, y H. C. S. Rughooputh, “Comparison of NSGA-II and SPEA2 on the Multiobjective Environmental/Economic Dispatch Problem”, University of Mauritius Research Journal, vol. 16, núm. 1, pp. 485–511, 2010.; L. Atmaniou et al., “A multiobjective genetic algorithm optimization framework for batch plant design”, Computer Aided Chemical Engineering, vol. 15, núm. C, pp. 400–405, 2003, doi:10.1016/S1570-7946(03)80577-1.; C. Gutérrez-Antonio, A. Briones-Ramírez, y A. Jiménez-Gutiérrez, “Optimization of Petlyuk sequences using a multi objective genetic algorithm with constraints”, Comput Chem Eng, vol. 35, núm. 2, pp. 236–244, 2011, doi:10.1016/j.compchemeng.2010.10.007.; A. I. Papadopoulos y P. Linke, “Multiobjective molecular design for integrated process-solvent systems synthesis”, AIChE Journal, vol. 52, núm. 3, pp. 1057–1070, 2006, doi:10.1002/aic.10715.; S. Ekins, J. D. Honeycutt, y J. T. Metz, “Evolving molecules using multi-objective optimization: Applying to ADME/Tox”, Drug Discov Today, vol. 15, núm. 11–12, pp. 451–460, 2010, doi:10.1016/j.drudis.2010.04.003.; L. Y. Ng, N. G. Chemmangattuvalappil, y D. K. S. Ng, “A multiobjective optimization-based approach for optimal chemical product design”, Ind Eng Chem Res, vol. 53, núm. 44, pp. 17429–17444, 2014, doi:10.1021/ie502906a.; P. Bigus, J. Namieśnik, y M. Tobiszewski, “Application of multicriteria decision analysis in solvent type optimization for chlorophenols determination with a dispersive liquid-liquid microextraction”, J Chromatogr A, vol. 1446, pp. 21–26, 2016, doi:10.1016/j.chroma.2016.03.065.; C. M. Fonseca y P. J. Fleming, “Genetic Algorithms for Multi-Objective Optimization: Formulation, discussion and generalization”, en Proceedings of the 5th International Conference on Genetic Algorithms, 1993, pp. 416–423. doi:10.3156/jfuzzy.9.4_471_1.; M. Garza-Fabre, G. T. Pulido, y C. A. C. Coello, “Ranking methods for many-objective optimization”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5845 LNAI, pp. 633–645, 2009, doi:10.1007/978-3-642-05258-3_56.; K. Deb y H. Jain, “An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints”, IEEE Transactions on Evolutionary Computation, vol. 18, núm. 4, pp. 577–601, 2014, doi:10.1109/TEVC.2013.2281535.; H. Ishibuchi, N. Tsukamoto, y Y. Nojima, “Evolutionary many-objective optimization: A short review”, 2008 IEEE Congress on Evolutionary Computation, CEC 2008, pp. 2419–2426, 2008, doi:10.1109/CEC.2008.4631121.; H. Sato, “Pareto Partial Dominance MOEA in Many-Objective Optimization”, Search (Syd), núm. January, pp. 1–10, 2009.; H. Aguirre y K. Tanaka, “Many-objective optimization by space partitioning and adaptive ∈-ranking on MNK-landscapes”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5467 LNCS, pp. 407–422, 2010, doi:10.1007/978-3-642-01020-0_33.; C. H. Papadimitriou y M. Yannakakis, “On the approximability of trade-offs and optimal access of web sources”, Annual Symposium on Foundations of Computer Science - Proceedings, pp. 86–92, 2000, doi:10.1109/sfcs.2000.892068.; T. Erlebach, H. Kellerer, y U. Pferschy, “Approximating Multi-objective Knapsack Problems”, pp. 210–211, 2001.; J. Bader y E. Zitzler, “HypE : An algorithm for fast optimization”, Evol Comput, vol. 19, núm. 1, pp. 45–76, 2011.; L. While, P. Hingston, L. Barone, y S. Huband, “A faster algorithm for calculating hypervolume”, IEEE Transactions on Evolutionary Computation, vol. 10, núm. 1, pp. 29–38, 2006, doi:10.1109/TEVC.2005.851275.; K. Bringmann y T. Friedrich, “Approximating the volume of unions and intersections of high-dimensional geometric objects”, Comput Geom, vol. 43, núm. 6–7, pp. 601–610, 2010, doi:10.1016/j.comgeo.2010.03.004.; X. Cai, H. Sun, y Z. Fan, “A diversity indicator based on reference vectors for many-objective optimization”, Inf Sci (N Y), vol. 430–431, pp. 467–486, 2018, doi:10.1016/j.ins.2017.11.051.; G. Dai, C. Zhou, M. Wang, y X. Li, “Indicator and reference points co-guided evolutionary algorithm for many-objective optimization problems”, Knowl Based Syst, vol. 140, pp. 50–63, 2018, doi:10.1016/j.knosys.2017.10.025.; M. Zhang y H. Li, “A reference direction and entropy based evolutionary algorithm for many-objective optimization”, Applied Soft Computing Journal, vol. 70, pp. 108–130, 2018, doi:10.1016/j.asoc.2018.05.011.; J. Zou, C. Ji, S. Yang, Y. Zhang, J. Zheng, y K. Li, “A knee-point-based evolutionary algorithm using weighted subpopulation for many-objective optimization”, Swarm Evol Comput, vol. 47, núm. January, pp. 33–43, 2019, doi:10.1016/j.swevo.2019.02.001.; Y. Liu, N. Zhu, K. K. Li, M. Li, J. Zheng, y K. Li, “An angle dominance criterion for evolutionary many-objective optimization”, Inf Sci (N Y), núm. xxxx, 2019, doi:10.1016/j.ins.2018.12.078.; L. Cai, S. Qu, y G. Cheng, “Two-archive method for aggregation-based many-objective optimization”, Inf Sci (N Y), vol. 422, pp. 305–317, 2018, doi:10.1016/j.ins.2017.08.078.; P. J. Fleming, R. C. Purshouse, y R. J. Lygoe, “Many-objective optimization: An engineering design perspective”, Lecture Notes in Computer Science, vol. 3410, pp. 14–32, 2005, doi:10.1007/978-3-540-31880-4_2.; A. Inselberg y B. Dimsdale, “Parallel coordinates: A tool for visualizing multi-dimensional geometry”, pp. 361–378, 1990, doi:10.1007/978-4-431-68057-4_3.; A. Pryke, S. Mostaghim, y A. Nazemi, “Heatmap visualization of population based multi objective algorithms”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4403 LNCS, pp. 361–375, 2007, doi:10.1007/978-3-540-70928-2_29.; D. J. Walker, R. M. Everson, y J. E. Fieldsend, “Visualizing mutually nondominating solution sets in many-objective optimization”, IEEE Transactions on Evolutionary Computation, vol. 17, núm. 2, pp. 165–184, 2013, doi:10.1109/TEVC.2012.2225064.; P. Hoffman y G. Grinstein, “Visualizations for High Dimensional Data Mining-Table Visualizations”, núm. August 2001, 1997.; J. B. Tenenbaum, V. De Silva, y J. C. Langford, “A global geometric framework for nonlinear dimensionality reduction”, Science (1979), vol. 290, núm. 5500, pp. 2319–2323, 2000, doi:10.1126/science.290.5500.2319.; J. Zou, L. Fu, J. Zheng, S. Yang, G. Yu, y Y. Hu, “A many-objective evolutionary algorithm based on rotated grid”, Applied Soft Computing Journal, vol. 67, pp. 596–609, 2018, doi:10.1016/j.asoc.2018.02.031.; B. Khan, S. Hanoun, M. Johnstone, C. P. Lim, D. Creighton, y S. Nahavandi, “A scalarization-based dominance evolutionary algorithm for many-objective optimization”, Inf Sci (N Y), vol. 474, pp. 236–252, 2019, doi:10.1016/j.ins.2018.09.031.; J. Zou, Y. Zhang, S. Yang, Y. Liu, y J. Zheng, “Adaptive neighborhood selection for many-objective optimization problems”, Applied Soft Computing Journal, vol. 64, pp. 186–198, 2018, doi:10.1016/j.asoc.2017.11.041.; M. Wagner y F. Neumann, “A Fast Approximation-Guided Evolutionary Multi-Objective Algorithm”, pp. 687–694.; Q. Zhang, S. Member, y H. Li, “MOEA / D : A Multiobjective Evolutionary Algorithm Based on Decomposition”, vol. 11, núm. 6, pp. 712–731, 2007.; I. Giagkiozis, R. C. Purshouse, y P. J. Fleming, “Generalized Decomposition and Cross Entropy Methods for Many-Objective Optimization”, Inf Sci (N Y), p. 2014, 2014, doi:10.1016/j.ins.2014.05.045.; H. Seada y K. Deb, “U-NSGA-III : A Unified Evolutionary Algorithm for Single , Multiple , and Many-Objective Optimization”, pp. 1–30.; D. Weininger, “SMILES, a Chemical Language and Information System: 1: Introduction to Methodology and Encoding Rules”, J Chem Inf Comput Sci, vol. 28, núm. 1, pp. 31–36, 1988, doi:10.1021/ci00057a005.; L. Hornos, “Introducción a SMILES: Dibujando moléculas en el bloc de notas”, El problema de describir una estructura molecular con caracteres comunes, 2020.; Daylight Chemical Information Systems Inc., “SMILES - A Simplified Chemical Language”, -, 2019.; N. M. O. Boyle, “Towards a Universal SMILES representation - A standard method to generate canonical SMILES based on the InChI”, pp. 1–14, 2012.; IUPAC, “Definición de compuestos anti aromáticos”. https://goldbook.iupac.org/terms/view/A00382; A. T. M. G. Mostafa, J. M. Eakman, M. M. Montoya, y S. L. Yarbro, “Prediction of Heat Capacities of Solid Inorganic Salts from Group Contributions”, pp. 343–348, 1996.; D. W. Van Krevelen, Properties of Polymers: Their Correlation with Chemical Structure; their Numerical Estimation and Prediction from Additive Group Contributions. 2009.; D. Saracino, Abstract Algebra A First Course. 2008.; Joseph A. Gallian, Contemporary Abstract Algebra. 2013.; D. B. Fraleigh, A first course in abstract algebra. 2002.; W. L. Kocay y D. L. Kreher, Graphs, Algorithms, and Optimization, vol. 1. Boca Raton, FL, USA: CRC Press, 2017.; P. Fernández-Gallardo y J. L. Fernández-Pérez, “La Teoría de Pólya”, en El discreto encanto de la matemática, 2002, pp. 1133–1145.; A. R. Matamala, “PÓLYA’S COMBINATORIAL METHOD AND THE ISOMER ENUMERATION PROBLEM”, Bol. Soc. Chil. Quím., 2002. https://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0366-16442002000200006#17; S. Pevac y G. Crundwell, “Pólya’s Isomer Enumeration Method: A Unique Exercise in Group Theory and Combinatorial Analysis for Undergraduates”, J Chem Educ, vol. 77, núm. 10, pp. 1358–1360, 2000, doi:10.1021/ed077p1358.; R. L. Apodaca, “A Comprehensive Treatment of Aromaticity in the SMILES Language”, 2021. https://depth-first.com/articles/2020/02/10/a-comprehensive-treatment-of-aromaticity-in-the-smiles-language/; Daylight Chemical Information Systems Inc., “SMILES Tutorial: Conventions”. https://www.daylight.com/meetings/summerschool98/course/dave/smiles-convent.htm; E. C. Ihmels y J. Gmehling, “Extension and revision of the group contribution method GCVOL for the prediction of pure compound liquid densities”, Ind Eng Chem Res, vol. 42, núm. 2, pp. 408–412, 2003, doi:10.1021/ie020492j.; T. J. Sheldon, C. S. Adjiman, y J. L. Cordiner, “Pure component properties from group contribution: Hydrogen-bond basicity, hydrogen-bond acidity, Hildebrand solubility parameter, macroscopic surface tension, dipole moment, refractive index and dielectric constant”, Fluid Phase Equilib, vol. 231, núm. 1, pp. 27–37, 2005, doi:10.1016/j.fluid.2004.12.017.; J. Gmehling, J. Lohmann, A. Jakob, J. Li, y R. Joh, “A modified UNIFAC (Dortmund) model. 4. Revision and extension”, Ind Eng Chem Res, vol. 37, núm. 12, pp. 4876–4882, 1998, doi:10.1021/ie980347z.; D. Constantinescu y J. Gmehling, “Further development of modified UNIFAC (Dortmund): Revision and extension 6”, J Chem Eng Data, vol. 61, núm. 8, pp. 2738–2748, 2016, doi:10.1021/acs.jced.6b00136.; A. Fredeslund, Russell L. Jones, y J. M. Prausnitz, “Group-Contri bution Estimation of Activity Coefficients in Nonideal Liquid Mixtures”, vol. 21, núm. 6, 1975.; Dortmund-Databank, “Published ParametersUnifac”. http://www.ddbst.com/published-parameters-unifac.html; J. J. Irwin y B. K. Shoichet, “ZINC - A free database of commercially available compounds for virtual screening”, J Chem Inf Model, vol. 45, núm. 1, pp. 177–182, 2005, doi:10.1021/ci049714+.; T. Sterling y J. J. Irwin, “ZINC 15 - Ligand Discovery for Everyone”, J Chem Inf Model, vol. 55, núm. 11, pp. 2324–2337, 2015, doi:10.1021/acs.jcim.5b00559.; EPA, “Distributed Structure-Searchable Toxicity (DSSTox) Database”, 2022. https://www.epa.gov/chemical-research/distributed-structure-searchable-toxicity-dsstox-database.; Texas A&M University Libraries, “Chemical Pricing Database - Beta Version”, 2022. https://tamu.libguides.com/c.php?g=587308&p=5694124&url=L2V2LTI5ODk3NjIvZGIvNTUzNTQvdmlldy5hc3B4; S&P Global, “Chemical Week by S&P Global”, 2022. https://chemweek.com/home; Relx Inc., “ICIS Chemical Bussiness”, 2022. https://www.icis.com/subscriber/specialpublications/#_=_; T. Group, G. All, I. N. D. Farm, P. F. F. Farm, y G. Smith, “Table 9 . Producer price indexes for commodity and service groupings and individual items , not seasonally adjusted [April 2022, Index base 1982=100, unless otherwise indicated]”, núm. April, pp. 1–58, 2022.; S. Müller, “GitHub - Simon Müller - Fragmentation Algorithm Paper”, https://github.com/simonmb/fragmentation_algorithm_paper, 2023. https://github.com/simonmb/fragmentation_algorithm_paper (consultado el 8 de abril de 2023).; S. Müller, “Flexible heuristic algorithm for automatic molecule fragmentation: Application to the UNIFAC group contribution model”, J Cheminform, vol. 11, núm. 1, 2019, doi:10.1186/s13321-019-0382-3.; J. Prieto y J. Gomez, “Hybrid Adaptive Evolutionary Algorithm for Multi-objective Optimization”, 2020, [En línea]. Disponible en: http://arxiv.org/abs/2004.13925; DDBST GmbH, “Parameters of the Modified UNIFAC (Dortmund) Model”, 2022. http://unifac.ddbst.de/PublishedParametersUNIFACDO.html; OEIS.org, “The On-Line Encyclopedia of Integer Sequences® (OEIS®)”, https://oeis.org/, 2023. https://oeis.org/ (consultado el 25 de julio de 2023).; N. C. for B. I. NIH - National Library of Medicine, “PubChem: Explore Chemistry - Quickly find chemical information from authoritative sources”, 2023.; J. Gómez, “Hybrid Adaptive Evolutionary Algorithm Hyper Heuristic”, pp. 1–5.; Inc. Daylight Chemical Information System, “SMARTS - A Language for Describing Molecular Patterns”, https://www.daylight.com/dayhtml/doc/theory/theory.smarts.html, 2019. https://www.daylight.com/dayhtml/doc/theory/theory.smarts.html (consultado el 8 de abril de 2023).; U. H. ZBH - Center for Bioinformatics, “SMARTS PLUS”, https://smarts.plus/, 2023. https://smarts.plus/ (consultado el 8 de abril de 2023).; U. Weidlich y J. Gmehling, “A Modified UNIFAC Model. 1. Prediction of VLE, hE, and 3∞”, Ind Eng Chem Res, vol. 26, núm. 7, pp. 1372–1381, 1987, doi:10.1021/ie00067a018.; A. Ag, Ε. Fredenslund, J. Gmehling, y P. Rasmussen, Vapor-liquid equilib using UNIFAC a group-contribution method Library ol Congress Cataloging in Publication Data. 1977.; ACD Labs, “ACD Labs ChemSketch”, https://www.acdlabs.com/resources/free-chemistry-software-apps/chemsketch-freeware/, 2023. https://www.acdlabs.com/resources/free-chemistry-software-apps/chemsketch-freeware/ (consultado el 13 de julio de 2022).; https://repositorio.unal.edu.co/handle/unal/85692; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

  7. 7

    Relation: Lucas, Solange Maria Fortuna - Gestão da incerteza em problemas de programação linear multi-objectivo com coeficientes intervalares. Coimbra, 2007.

  8. 8

    Popis súboru: pdf; application/pdf

    Relation: Congreso Internacional de Electrónica Control y Telecomunicaciones.; Borrero Guerrero, H., Baquero Velasquez, A.E., Barrero, J.F., Côco, D.Z., Risardi, J.C., Magalhães, D.V. and Becker, M., 2014. “Orientation (yaw) fuzzy controller applied to a car-like mobile robot prototype”. In 2014 IEEE 5th Colombian Workshop on Circuits and Systems (CWCAS). pp. 1–6. doi:10.1109/CWCAS.2014.6994603.; Higuti, V.A.H., Guerrero, H.B., Velasquez, A.E.B., Pinto, R., Tinelli, L.M., Magalhães, D.V. and Milori, D., 2015. “Lowcost embedded computer for mobile robot platform based on raspberry board”. In ABCM International Congress of Mechanical Egineering (Cobem2015), Rio de Janeiro, Brazil.; Guerrero, H.B., 2016. Desenvolvimento de um sistema de controle em um robô móvel agrícola em escala reduzida para deslocamento entre fileiras de plantio. Ph.D. thesis, Escola de Engenharia de São Carlos, Universidad de Sao Paulo.; Guerrero, H.B., 2016. Desenvolvimento de um sistema de controle em um robô móvel agrícola em escala reduzida para deslocamento entre fileiras de plantio. Ph.D. tesis, Escola de Engenharia de São Carlos, Universidad de Sao Paulo.; Ni, J., Wang, Y., Li, H. and Du, H., 2022. “Path tracking motion control method of tracked robot based on improved lqr control”. 2022 41st Chinese Control Conference (CCC). doi:10.23919/CCC55666.2022.9902113.; Ben Halima Abid, D., Allagui, N.Y. and Derbel, N., 2017. “Navigation and trajectory tracking of mobile robot based on kinematic pi controller”. In 2017 18th International Conference on Sciences and; Allagui, N.Y., Abid, D.B. and Derbel, N., 2019. “Autonomous navigation of mobile robot with combined fractional order pi and fuzzy logic controllers”. In 2019 16th International Multi-Conference on Systems, Signals Devices (SSD). pp. 78–83. Doi:10.1109/SSD.2019.8893176.; Lentin, J., 2018. “Robot operating system for absolute beginners”. Apress, Berkeley, CA.; Nevludov, I., Sychova, O., Reznichenko, O., Novoselov, S., Mospan, D. and Mospan, V., 2021. “Control system for agricultural robot based on ros”. 2021 IEEE International Conference on Modern Electrical and Energy Systems (MEES). pp. 1–6. doi:10.1109/MEES52427.2021.9598560.; Megalingam, R.K., Nagalla, D., Nigam, K., Gontu, V. and Allada, P.K., 2020. “Pid based locomotion of multi-terrain robot using ros platform”. 2020 Fourth International Conference on Inventive Systems and Control (ICISC). pp. 751–755. doi:10.1109/ICISC47916.2020.9171152.; Alam Bhuiyan, Ifte Khairul. (2017). LiDAR Sensor for Autonomous Vehicle. 10.13140/RG.2.2.16982.34887/1.; Lin, Z., Xiong, Y., Dai, H. and Xia, X., 2017. “An experimental performance evaluation of the orientation accuracy of four nine-axis mems motion sensors”. 2017 5th International Conference on Enterprise Systems (ES). pp. 185–189. doi:10.1109/ES.2017.37.; Henry, B.G., David, Q.Y., Estivent, C.M.J., Arbey, C.C.L., Alexis, C.R.Y. and Andrés, S.R., 2020. “Lidar readings based mobile robot wall-following task using a reactive fuzzy control system - a low-cost experimental approach”. URL https://hemeroteca.unad.edu.co/index.php/memorias/article/view/4201.; Guerrero, H.B., 2016. Desenvolvimento de um sistema de controle em um robô móvel agrícola em escala reduzida para deslocamento entre fileiras de plantio. Ph.D. tesis, Escola de Engenharia de São Carlos, Universidade de Sao Paulo.; S.N. Sivanandam, S. Sumathi. and S.N. Deepa, "Introduction to Fuzzy Logic using MATLAB", Springer-Verlag, Berlin, Germany, 2007.; M. Garcia Sanz and M. Motilva Casado, "Herramientas para el estudio de robots de cinemática paralela: Simulador y prototipo experimental," Revista Iberoamericana de Automática e Informática Industrial, RIAI, vol. 2, no. 2, pp. 73-81, 2005. https://polipapers.upv.es/index.php/RIAI/article/view/8064; A. I. Aureles Cabrera, Robot paralelo tipo STEWART para la rehabilitación de tobillo, Hidalgo, Mexico: Universidad Politécnica de Tulancingo, 2019. http://www.upt.edu.mx/Contenido/Investigacion/Contenido/TESIS/MAC/2019/MAC_T_2 019_01_AAC.pdf; Instituto de Investigación de Seguridad en la Conducción IOWA, «Simulador NADS - 1,» Univesidad de Iowa, 2023. [En línea]. Available: https://dsri.uiowa.edu/nads-1. [Último acceso: 02 2023].; SIMAERO, "AIRBUS A340 FFS," SIMAERO, 2023. [Online]. Available: https://www.sim.aero/a340/. [Último acceso 02 2023].; O. Altuzarra, Y. San Martín, E. Amezua and A. Hernández, "Motion pattern analysis of parallel kinematic machines: A case study," Robotics and Computer-Integrated Manufacturing, vol. 25, no. 2, pp. 432-440, 2009. https://doi.org/10.1016/j.rcim.2008.01.007; J. Fernandes and A. Selvakumar, "Kinematic and Dynamic Analysis of 3PUU Parallel Manipulator for Medical Applications," Procedia Computer Science, vol. 133, no. 1, pp. 604-611, 2018. https://doi.org/10.1016/j.procs.2018.07.091; I. Ben Hamida, M. Amine Laribi, A. Mlika, L. Romdhane, S. Zeghloul and G. Carbone, "Multi-Objective optimal design of a cable driven parallel robot for rehabilitation tasks," Mechanism and Machine Theory, vol. 156, no. 1, pp. 104-141, 2021. https://doi.org/10.1016/j.mechmachtheory.2020.104141; K. Duarte Barón and C. Borrás Pinilla, «Generalidades de robots paralelos,» Revista visión electrónica, algo más que un estado sólido, vol. 10, nº 1, pp. 1-11, 2016. https://doi.org/10.14483/22484728.11711; K. Duarte Barón, C. Borrás Pinilla and J. J. Gil Pelaez, «Dynamic analysis and simulation of computed torque control of a parallel robot 3SPS - 1U,» de IEEE 4th Colombian Conference on Automatic Control (CCAC), Medellín, Colombia, 2019. https://doi.org/10.1109/CCAC.2019.8921238; C. Gosselin and J. Angeles, "Singularity analysis of closed-loop kinematic chains," IEEE Transactions on Robotics and Automation, vol. 6, no. 3, pp. 281-290, 1990. https://doi.org/10.1109/70.56660; J. Kardos, "Robust Computed Torque Method of Robot Tracking Control," in 22nd International Conference on Process Control (PC19), Strbske Pleso, Slovakia, 2019. https://doi.org/10.1109/PC.2019.8815088; C. Jun and W. Lin, "Track Tracking of Double Joint Robot Based on Sliding Mode Control," in IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE), Dalian, China, 2020. https://doi.org/10.1109/ICISCAE51034.2020.9236895; W. X. Xu, G. Z. Cao, Y. P. Zhang, J. C. Chen, D. P. Tan and Z. Q. Ling, "Adaptive backstepping sliding mode control of lower limb exoskele-ton robot based on combined double power reaching law," in 2th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Baishan, China, 2022. https://doi.org/10.1109/CYBER55403.2022.9907279; X. Chen, H. Chen, Y. Huang and Q. Huang, "Adaptability Control Towards Complex Ground Based on Fuzzy Logic for Humanoid Robots," IEEE Transactions on Fuzzy Systems, vol. 30, no. 6, pp. 1574-1584, 2022. https://doi.org/10.1109/TFUZZ.2022.3167458; D. Li, J. Pan, J. Liu, M. Wang and J. Yu, "Model Predictive Control Based Path Following of an Amphibious Robot," in 0th Chinese Control Conference (CCC), 2021. https://doi.org/10.23919/CCC52363.2021.9549348; Y. Zhang, L. Sol and Y. Zhang, "Research on Algorithm of Humanoid Robot Arm Control System Based on Fuzzy PID Control," in International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS), Bristol, United Kingdom, 2022. https://doi.org/10.1109/AIARS57204.2022.00082; K. Duarte Barón and C. Borrás Pinilla, Analisis, diseño y simulacion de un control robusto para un robot paralelo de 3 grados de libertad, Bucaramanga, Colombia, Universidad Industrial de Santander, 2019. https://noesis.uis.edu.co/items/c91bc6a4-e228-44f8- 8ab4-33000e9e8688; J. J. Slotine and W. Li, Applied nonlinear control, New Jersey: Prentice Hall, 1991.; S. Iqbal and A. I. Bhatti, "Robust sliding-mode controller design for a stewart platform," in Proceedings of International Bhurban Conference on Applied Sciences, Islamabad, Pakistan, 2007. https://doi.org/10.1109/IBCAST.2007.4379924; C. Zhang and L. Zhang, "Kinematics analysis and workspace investigation of a novel 2- DOF parallel manipulator applied in vehicle driving simulator," Robotics and ComputerIntegrated Manufacturing, vol. 29, no. 2, pp. 113-120, 2013. https://doi.org/10.1016/j.rcim.2012.11.005; Hongwei Gao, Jin An, Chee Kai Chua, David Bourell, Che-Nan Kuo, Dawn T.H. Tan, 3D printed optics and photonics: Processes, materials and applications, Materials Today, 2023, ISSN 1369-7021, https://doi.org/10.1016/j.mattod.2023.06.019; C. Wu, L. Wu, G. Shang and H. Guo, "Application and Research of 3D Printing Technology in the Field of Architecture," 2021 4th International Conference on Electron Device and Mechanical Engineering (ICEDME), Guangzhou, China, 2021, pp. 71-74, https://doi.org/10.1109/ICEDME52809.2021.00024; Jens Oprel, Gerjan Wolterink, Jurnan Schilder, Gijs Krijnen, Novel 3D printed capacitive shear stress sensor, Additive Manufacturing, Volume 73, 2023, 103674, ISSN 2214- 8604, https://doi.org/10.1016/j.addma.2023.103674; Jun Ren, Fan Wu, Erwei Shang, Dongya Li, Yu Liu, 3D printed smart elastomeric foam with force sensing and its integration with robotic gripper, Sensors and Actuators A: Physical, Volume 349, 2023, 113998, ISSN 0924-4247, https://doi.org/10.1016/j.sna.2022.113998; Guo Liang Goh, Wai Yee Yeong, Jannick Altherr, Jingyuan Tan, Domenico Campolo, 3D printing of soft sensors for soft gripper applications, Materials Today: Proceedings, Volume 70, 2022, Pages 224-229, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2022.09.025; W. Zhang, J. Li, H. Liu and G. Jin, "Research on Embedded 3D Printing for Magnetic Soft Robots," 2021 IEEE 16th International Conference on Nano/Micro Engineered and Molecular Systems (NEMS), Xiamen, China, 2021, pp. 518-523, https://doi.org/10.1109/NEMS51815.2021.9451436; M. Abouelmajd, A. Bahlaoui, I. Arroub, M. Lagache and S. Belhouideg, "Mechanical Characterization of PLA Used in Manufacturing of 3D Printed Medical Equipment for COVID-19 Pandemic," 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), Kenitra, Morocco, 2020, pp. 1-5, https://doi.org/10.1109/ICECOCS50124.2020.9314444; S. Zhang, G. Xia, X. Hao, Y. Zhang, W. Chen and Z. Zhou, "Design Optimization and Simulation Analysis of Screw Extrusion 3D Printing Screw," 2022 5th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM), Ma'anshan, China, 2022, pp. 400-404, https://doi.org/10.1109/WCMEIM56910.2022.10021447; B. B. Kanbur, S. Shen, Y. Zhou and F. Duan, "Neural network-integrated multiobjective optimization of the 3D-printed conformal cooling channels," 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech), Split, Croatia, 2020, pp. 1-6, https://doi.org/10.23919/SpliTech49282.2020.9243730; D. Wang, H. Wang and Y. Wang, "Continuity Path Planning for 3D Printed Lightweight Infill Structures," 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS), Shenyang, China, 2021, pp. 959-962, https://doi.org/10.1109/TOCS53301.2021.9688877; M. H. Ali, G. Yerbolat and S. Amangeldi, "Material Optimization Method in 3D Printing," 2018 IEEE International Conference on Advanced Manufacturing (ICAM), Yunlin, Taiwan, 2018, pp. 365-368, https://doi.org/10.1109/AMCON.2018.8614886; R F. Peng, "Prototyping to Mass Production: Automated CAD Model and G-Code Optimization Framework for Industrial 3D Printing," 2023 9th International Conference on Mechatronics and Robotics Engineering (ICMRE), Shenzhen, China, 2023, pp. 203- 206, https://doi.org/10.1109/ICMRE56789.2023.10106588; Mohit Bhayana, Jaswinder Singh, Ankit Sharma, Manish Gupta, A review on optimized FDM 3D printed Wood/PLA bio composite material characteristics, Materials Today: Proceedings, 2023, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2023.03.029; Aliza Rabinowitz, Paul M. DeSantis, Cemile Basgul, Hannah Spece, Steven M. Kurtz, Taguchi optimization of 3D printed short carbon fiber polyetherketoneketone (CFR PEKK), Journal of the Mechanical Behavior of Biomedical Materials, Volume 145, 2023, 105981, ISSN 1751-6161, https://doi.org/10.1016/j.jmbbm.2023.105981; Mihir Mogra, Ofer Asaf, Aaron Sprecher, Oded Amir, Design optimization of 3D printed concrete elements considering buildability, Engineering Structures, Volume 294, 2023, 116735, ISSN 0141-0296, https://doi.org/10.1016/j.engstruct.2023.116735; C. Wu, C. Dai, G. Fang, Y. -J. Liu and C. C. L. Wang, “General Support-Effective Decomposition for Multi-Directional 3-D Printing”, IEEE Transactions on Automation Science and Engineering, vol. 17, no. 2, pp. 599-610, April 2020, doi: https://doi.org/10.1109/TASE.2019.2938219; L. Cheng and A. To, “Part-scale build orientation optimization for minimizing residual stress and support volume for metal additive manufacturing: Theory and experimental validation,” Computer-Aided Design, vol. 113, pp. 1–23, Aug. 2019, doi: https://doi.org/10.1016/j.cad.2019.03.004; J. Jiang, X. Xu, and J. Stringer, “Optimization of process planning for reducing material waste in extrusion based additive manufacturing,” Robotics and Computer-Integrated Manufacturing, vol. 59, pp. 317–325, Oct. 2019, doi: https://doi.org/10.1016/j.rcim.2019.05.007; George E. P. Box. “Evolutionary Operation: A Method for Increasing Industrial Productivity.” Journal of the Royal Statistical Society. Series C (Applied Statistics) 6, no. 2 (1957): 81–101. https://doi.org/10.2307/2985505; J. C. Guacheta-Alba, S. Gonzalez, D. A. Nunez, M. Mauledoux, O. Aviles, "3D printing part orientation optimization: discrete approximation of support volume". International Journal of Electrical and Computer Engineering, vol 12. pp. 5958-5966, 2022. https://doi.org/10.11591/ijece.v12i6.pp5958-5966; L. Wing-Yue Geoffrey , M. Sharaf and N. Goldie, "Human-Robot Interaction for Rehabilitation Robots," in Robotic Assistive Technologies: Principles and Practice, Boca Raton, CRC Press, Taylor & Francis Group, 2017, pp. 26-27, 40.; C. Bodine, L. Sliker, M. Marquez, C. Clark, B. Burne and J. Sandstrum, "Social Assistive Robots for Children with Complex Disabilities," in Robotic Assitive Tecnologies: Principles and Practice, Boca Raton, CRC Press, Taylor & Francis Group, 2017, pp. 263, 295.; R. Baker, "Gait analysis methods in rehabilitation," J. Neuroeng. Rehabil., vol. 3, p. 4, 2006.; J. C. Pulido, C. Suárez-Mejías, J. C. González, A. Dueñas Ruiz, P. Ferrand Ferri, M. E. Martínez Sahuquillo, C. Echevarría Ruiz De Vargas, P. Infante-Cossio and C. L. Parra Calderón, "A Socially Assistive Robotic Platform for Upper-Limb Rehabilitation," IEEE ROBOTICS & AUTOMATION MAGAZINE, pp. 24-39, 2019.; G. Emre Cemal, C. YuJung and K. ChangHwan , "Imitation of Human Upper-Body Motions by Humanoid Robots," 16th International Conference on Ubiquitous Robots (UR), p. 24, 2019.; K. Darvish, L. Penco, J. Ramos, R. Cisneros, J. Pratt, E. Yoshida, S. Ivaldi and D. Pucci, "Teleoperation of Humanoid Robots: A Survey," Computer Science, pp. 1-21, 202.; J. Valčík, Similarity Models for Human Motion Data, Brno: Masaryk University, 2016.; P. Kopniak, "Motion capture using multiple Kinect controllers," Przeglad. Elektrotechniczny, 91(8), pp. 26-29, 2015.; L. L. Gómez Echeverry, A. M. Jaramillo Henao, M. A. Ruiz Molina, S. . M. Velásquez Restrepo, C. A. Páramo Velásquez and G. J. Silva Bolívar, "Human motion capture and analysis systems: a systematic review," PROSPECTIVA Vol. 16 - No. 2, pp. 24-34, 2018.; N. Ltda., Axis Neuron User Guide.; A. M. Norjasween, F. A. khtar Hanapiah, R. A. Abdul Rahman and H. Yussof, "Emergence of Socially Assistive Robotics in Rehabilitation for Children with Cerebral Palsy: A Review," International Journal of Advanced Robotic Systems, pp. 1-7, 2016.; S. Fojt˚u, "Nao Localization and Navigation Based on Sparse 3D Point Cloud Reconstruction," CZECH TECHNICAL UNIVERSITY IN PRAGUE, Praga, 2011.; Revista de Robots, "ROBOT NAO PARA EMPRESA Y EDUCACIÓN," Revista de Robots, 8 junio 2023. [Online]. Available: https://revistaderobots.com/robots-y-robotica/robot-naocaracteristicas-y-precio/?cn-reloaded=1. [Accessed 2023 junio 24].; University of Wisconsin-Madison, "Biovision BVH," 2023. [Online]. Available: https://research.cs.wisc.edu/graphics/Courses/cs-838-1999/Jeff/BVH.html.; B. Lutjens, "perc-neuron-ros-ur10," 2019. [Online]. Available: https://github.com/blutjens/perc_neuron_ros_ur10.; S. Haller, "perception-neuron-ros," 2017. [Online]. Available: https://github.com/smhaller/perception-neuron-ros.; O. Robotics, "Open Robotics," 2019. [Online]. Available: http://wiki.ros.org/nao.; C. Girard, D. Calderón de León, A. Arafat Lemus, V. Ferman and J. Fajardo, "A Motion Mapping System for Humanoids that Provides Immersive Teleprescence Experiences," Universidad Galileo, 2020.; B. M. Lütjens, "Real-Time Teleoperation of Industrial Robots with the Motion Capture System Perception Neuron," TECHNISCHE UNIVERSITÄT MÜNCHEN, Munich, 2017.; I. Almetwally and M. Mallem, "Real-time Tele-operation and Tele-walking of Humanoid Robot Nao using Kinect Depth Camera," IEEE, pp. 1-4, 2013.; C. Gu, L. Weicong, X. He, Z. Lei and Z. Mingming, "IMU-based motion capture system for rehabilitation applications: A systematic review," Biomimetic Intelligence and Robotics, vol. 3, no. 2, pp. 1-13, 2023.; Ministerio de Educación Nacional, «¿Cómo formular e implementar los resultados de aprendizaje?,» 2021. [En línea]. Available: https://www.mineducacion.gov.co/1780/articles-408425_recurso_5.pdf. [Último acceso: 12 septiembre 2023].; NASA, «Los Rovers del Marte,» 23 marzo 2021. [En línea]. Available: https://spaceplace.nasa.gov/mars-rovers/sp/. [Último acceso: 10 septiembre 2023].; J. J. Lugo, «Rover espacial SR-001 diseñado para descubrir nuevos mundos,» 2023. [En línea]. Available: https://ideasdi.com/diseno-transporte/rover-espacial-sr-001/. [Último acceso: 9 septiembre 2023].; TN, «La NASA diseñó un rover que hace rápel para desniveles de otros planetas,» 16 octubre 2020. [En línea]. Available: https://tn.com.ar/tecno/2020/10/16/la-nasadiseno-un-rover-que-hace-rapel-para-desniveles-de-otros-planetas/. [Último acceso: 12 septiembre 2023].; x. m. J. G. y. R. L. Christian Montaleza, «Diseño de un prototipo de robot con geometría Rocker-Bogie,» Enfoque UTE , vol. 13, nº 1, pp. 82-96, 2022.; M. R. H. S. y. M. Santos, «Primera aproximación de diseño de un rover minimalista bio-inspirado,» de XXXVII jornada de automatica, Madrid, 2016.; C. A. L. Talavera, «Diseño de un vehículo a tracción humana para participar en el NASA Human Rover Challenge,» 2022. [En línea]. Available: https://hdl.handle.net/20.500.12404/24409. [Último acceso: 9 septiembre 2023].; D. L. L. y. J. A. A. O. Diana Marcela Hernandez Rincón, «Diseño y construccion de un vehículo autónomo tipo rover -DIDAJO-,» 2005. [En línea]. Available: http://biblioteca.usbbog.edu.co:8080/Biblioteca/BDigital/37506.pdf. [Último acceso: 8 septiembre 2023].; H. . A. Carvajal Pulido, J. D. Bohórquez Guerra y G. Carrasquilla Mercado, «Diseño y construcción de un prototipo a escala de vehículo tipo rover no tripulado para la siembra, fumigación y transporte de productos agrícolas en terrenos irregulares del corregimiento de Berlín Santander,» junio 2021. [En línea]. Available: https://repository.unab.edu.co/handle/20.500.12749/14232. [Último acceso: 5 septiembre 2023].; Pavcowavin, «5 beneficios de usar tuberías PVC en tu casa,» 12 marzo 2021. [En línea]. Available: https://pavcowavin.com.co/blog/beneficios-de-usar-tuberiaspvc#:~:text=Las%20tuber%C3%ADas%20de%20policloruro%20de,como%20aguas %20lluvia%20y%20ventilaci%C3%B3n. [Último acceso: 6 septiembre 2023].; Electrotekmega, «Motor Reductor Faulhaber,» 2023. [En línea]. Available: https://electrotekmega.com/producto/motor-reductor-faulhaber/. [Último acceso: 10 septiembre 2023].; Mvelectronica, «Motorreductor Faulhaber Con Encoder De Velocidad 12v 64:1 120rpm 2342l012cr,» 2023. [En línea]. Available: https://mvelectronica.com/producto/motorreductor-faulhaber-con-encoder-develocidad-12v-64-1-120rpm-2342l012cr. [Último acceso: 2 septiembre 2023].; Arduino.cl, «Arduino Mega 2560,» 2023. [En línea]. Available: https://arduino.cl/producto/arduino-mega2560/#:~:text=Arduino%20Mega%20es%20una%20tarjeta,implementa%20el%20len guaje%20Processing%2FWiring. [Último acceso: 10 septiembre 2023].; Arduino Spain, «Arduino Mega características y specificaciones,» 14 julio 2023. [En línea]. Available: https://arduino-spain.site/arduino-mega/. [Último acceso: 12 septiembre 2023].; Naylampmechatronics, «TUTORIAL DE USO DEL MÓDULO L298N,» 2023. [En línea]. Available: https://naylampmechatronics.com/blog/11_tutorial-de-uso-delmodulo-l298n.html. [Último acceso: 12 septiembre 2023].; Eneka SA, «MÓDULOS COMUNICACIÓN,» 2023. [En línea]. Available: https://www.eneka.com.uy/robotica/modulos-comunicacion/m%C3%B3dulobluetooth-hc05- detail.html#:~:text=Este%20m%C3%B3dulo%20bluetooth%20nos%20permite,opera ci%C3%B3n%20de%20un%20puerto%20serial. [Último acceso: 5 septiembre 2023].; Ambientesoluciones, «PRODUCTOS / BATERÍAS AGM,» 2023. [En línea]. Available: https://www.ambientesoluciones.com/portal/producto/bateria-12v9ah#:~:text=Detalles%3A,y%20descarga%20lenta%20y%20profunda. [Último acceso: 12 septiembre 2023].; Mlstatic, «FL1290,» 2023. [En línea]. Available: https://http2.mlstatic.com/D_NQ_NP_718370-MLA48587476540_122021-O.webp. [Último acceso: 10 septiembre 2023].; Habacuc Flores, «DEVELOPMENT OF A ROVER VEHICLE WITH ROCKER-BOGIE SUSPENSION FOR AGRICULTURAL INSPECTION,» 5 octubre 2016. [En línea]. Available: https://www.youtube.com/watch?v=7B1DlB6RcLQ&t=29s. [Último acceso: 7 septiembre 2023].; F. Cugurullo, "Urban Artificial Intelligence: From Automation to Autonomy in the Smart City," 2020.; Y. Liu, Q. Shi, W. Guo, and W. Liao, "A Real-time, Mobile-object Detection Approach for Unmanned Aerial Vehicle Based Forest Fire Surveillance System," 2020.; P. Jiang, D. Ergu, F. Liu, Y. Cai, and B. Ma, "A Review of YOLO Algorithm Developments," 2022.; R. C. U. Chiroma, "Vehicle detection, counting, and classification in traffic videos: A survey," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 10, pp. 3773-3785, 2021.; M. A. H. Akhand, "Vehicle Recognition from License Plate Number using Deep Learning," arXiv preprint arXiv:1903.09203, 2019.; J. W. Coral López, C. A. Pulgarín Ortiz, S. E. Nope, and A. Barandica, "Identificación de camiones de carga en movimiento por visión artificial," Tesis de pregrado, Escuela de Ingeniería Eléctrica y Electrónica, Universidad del Valle.; Á. Ramajo Ballester, J. González Cepeda, J. M. Armingol Moreno, and A. de la Escalera Hueso, "Reidentificación de camiones mediante técnicas de deep learning," Informe técnico, Laboratorio de Sistemas Inteligentes, Universidad Carlos III de Madrid.; R. A. Gonzalez, R. E. Ferro, and D. Liberona, "Government and governance in intelligent cities, smart transportation study case in Bogotá Colombia," Ain Shams Engineering Journal, vol. 11, no. 1, pp. 25-34, 2020.; Unesco.org. (2023, abril 20). IA por el Planeta: Destacando las innovaciones de IA para la movilidad sostenible y las ciudades inteligentes. [En línea]. Disponible en: https://www.unesco.org/es/articles/ia-por-el-planeta-destacando-las-innovaciones-de-ia-parala-movilidad-sostenible-y-las-ciudades; Redalyc.org. (S/f). [En línea]. Disponible en: https://www.redalyc.org/journal/852/85259689013/html/. Recuperado el 7 de julio de 2023.; Gómez Zapata, C. A. (2019). "Reconocimiento de objetos del hogar, usando redes neuronales convolucionales para personas con discapacidad visual." Revista Científica de Ingeniería y Tecnología, 2(2), 1-10. Disponible en: https://dialnet.unirioja.es/descarga/articulo/7436051.pdf.; Murgui, J., & García-Sánchez, A. J. (2018). "Clasificación y reconocimiento de imágenes con redes neuronales para aplicaciones industriales." Disponible en: https://riunet.upv.es/bitstream/handle/10251/115464/Murgui.pdf?sequence=1; Olabe, X. B. (s/f). "Redes Neuronales Artificiales y Sus Aplicaciones." Disponible en: https://ocw.ehu.eus/pluginfile.php/40137/mod_resource/content/1/redes_neuro/contenidos/pd f/libro-del-curso.pdf. Recuperado el 8 de julio de 2023.; Ortiz, G., & Sánchez, A. I. (2020). "Emprendimiento y tecnologías de la información y la comunicación en Bogotá." Cuadernos de Administración, 36(67), 199-211.; Torres, J., & Acosta, H. (2019). "La innovación en el ecosistema emprendedor de Bogotá." Cuadernos de Administración, 35(64), 251-262.; Uribe, F., & Guzmán, J. (2021). "La colaboración público-privada en el fomento de la innovación en Bogotá: el caso de la identificación de objetos en el contexto vial." Revista Internacional de Gestión y Economía Aplicada, 11(1), 89-101.; Bogotá se destaca como una ciudad innovadora en el CityLab 2021. (2021). [En línea]. Disponible en: https://bogota.gov.co/internacional/bogota-se-destaca-como-una-ciudadinnovadora-en-el-citylab-2021; Ministerio de Transporte y Agencia Nacional de Seguridad Vial adoptan la metodología para establecer velocidad límite y reglamentan los planes de gestión de la velocidad %7C ANSV. (2023). [En línea]. Disponible en: https://ansv.gov.co/es/prensa-comunicados/9955; Parámetros e hiperparámetros en el Machine Learning %7C Codificando Bits. (2023). [En línea]. Disponible en: https://www.codificandobits.com/blog/parametros-hiperparametrosmachine-learning/; ¿Qué es el ajuste de hiperparámetros? - Explicación de los métodos de ajuste de hiperparámetros - AWS. (2023). [En línea]. Disponible en: https://aws.amazon.com/es/whatis/hyperparameter-tuning/; Análisis del flujo vehicular Generalidades. (s/f). [En línea]. Disponible en: https://sjnavarro.files.wordpress.com/2008/08/analisis-de-flujo-vehicular-cal-y-mayor.pdf; "INSTITUTO POLITÉCNICO NACIONAL ESCUELA SUPERIOR DE CÓMPUTO ESCOM “Cálculo del flujo vehicular mediante segmentación de imágenes.” (s/f). [En línea]. Disponible en: https://tesis.ipn.mx/bitstream/handle/123456789/21133/C%C3%A1lculo%20del%20flujo%20v ehicular%20mediante%20segmentaci%C3%B3n%20de%20im%C3%A1genes.pdf?sequence =5&isAllowed=y; Oscar Javier Reyes-Ortiz, Mejia, M., & Juan Sebastián Useche-Castelblanco. (2019). "TÉCNICAS DE INTELIGENCIA ARTIFICIAL UTILIZADAS EN EL PROCESAMIENTO DE IMÁGENES Y SU APLICACIÓN EN EL ANÁLISIS DE PAVIMENTOS." Revista EIA, 16(31), 189–207. Disponible en: https://www.redalyc.org/journal/1492/149258931014/html/; Secretaría Distrital de Movilidad. (2014). Movilidadbogota.gov.co. https://www.movilidadbogota.gov.co/web/; L. Salcedo, "YOLO (You Only Look Once): Detección de Objetos en Tiempo Real," Mi Diario Python, Mi Diario Python, 19 de septiembre de 2018. Disponible en: https://pythondiario.com/2018/09/yolo-you-only-look-once-deteccion-de.html [26] Y. Shao, D. Zhang, H. Chu, X. Zhang, and Y. Rao, "A Review of YOLO Object Detection Based on Deep Learning," 2021.; Konda et al., "Real-Time Traffic Sign Detection and Recognition Using YOLOv3 and OpenCV," 2020.; Bhasin, "Real-time Object Detection with YOLO, OpenCV and Python," 2019.; Suresh et al., "Object Detection with YOLO for Intelligent Traffic Monitoring System," 2020.; S. Siddiqui, "Traffic Sign Detection Using YOLO v3 with OpenCV," 2020.; Propia, "Esquema general de entrenamiento usado para reconocimiento de imágenes con YOLO," [Figura], 2023.; A. Sharma, J. Pathak, M. Prakash, and J. N. Singh, "Object Detection using OpenCV and Python," International Journal of Innovative Research in Computer and Communication Engineering, vol. 8, no. 6, pp. 2736-2741, 2020.; R. Fernandez, "Detección de rostros, caras y ojos con Haar Cascad," Cursos de Programación de 0 a Experto © Garantizados, 10 de enero de 2018. Disponible en: https://unipython.com/deteccion-rostros-caras-ojos-haar-cascad/; Administrador, "Como crear tu propio DETECTOR DE OBJETOS con Haar Cascade %7C Python y OpenCV," omes-va.com, OMES, 29 de julio de 2020. Disponible en: https://omesva.com/como-crear-tu-propio-detector-de-objetos-con-haar-cascade-python-y-opencv/; E. Ángel and J. Ambrogio, "ARTÍCULOS PRESENTADOS A RADI %7C TECNOLOGÍA DE LA INFORMACIÓN Y COMUNICACIÓN." Disponible en: https://confedi.org.ar/wpcontent/uploads/2020/12/Articulo1-RADI16.pdf; Propia, "Esquema general de entrenamiento usado para reconocimiento de imágenes con Haar Cascade," [Figura], 2023.; S. S. Rao, "Vehicle detection and identification using computer vision and deep learning techniques," IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 10, pp. 2827-2836, 2018.; M. E. Gavilán, "Procesamiento de Imágenes y Visión Artificial con MATLAB," MathWorks, 2021.; MathWorks, "Visión Artificial con MATLAB: Detección y seguimiento de objetos," MathWorks, 2013.; Propia, "Esquema general de entrenamiento usado para reconocimiento de imágenes con Visión por computadora sin usar Deep Learning," [Figura], 2023.; A. Jayasree, M. Vari, P. Vishnu, and S. Medimi, "A comparative study of YOLO and Haar Cascade algorithm for helmet and license plate detection of motorcycles," 2022. [En línea]. Disponible en: https://www.diva-portal.org/smash/get/diva2:1707864/FULLTEXT02; J. Lamichhane, J. Aubertot, G. Begg, A. Birch, P. Boonekamp, S. Dachbrodt, J. Grønbech, M. Hovmøller, J. Jensen, L. Jørgensen, J. Kiss, P. Kudsk, A. Moonen, J. Rasplus, M. Sattin, J. Streito, A. Messéan, “Networking of integrated pest management: A powerful approach to address common challenges in agriculture”, J. Crop Protection, vol. 89, no. 1, pp. 139- 151, 2016. Doi: https://doi.org/10.1016/j.cropro.2016.07.011.; S. Azfar, A. Nadeem, A. Basit, “Pest detection and control techniques using wireless sensor network: a review”, J. Entomology and Zoology Studies, vol 3, no. 2, pp. 92-99, Jan. 2015.; J. Pretty, Z. Bharucha, “Integrated pest management for sustainable intensification of agriculture in Asia and Africa”, Insects, vol 6, no. 1, pp. 152-182, Mar. 2015. Doi: https://doi.org/10.3390/insects6010152.; D. Arcega, W. Lee, C. Lu, Y. Wu, P. Shih, S. Chen, J. Chung, T. Lin, “Edge-based wireless imaging system for continuous monitoring of insect pests in a remote outdoor mango orchard”, Computers and Electronics in Agriculture, vol 211, no. 108019, 2023. Doi: https://doi.org/10.1016/j.compag.2023.; H. Zhang, T. Islam, W. Lio, “Integrated pest management programme for cereal blast fungus Magnaporthe oryzae”, J. Integrative Agriculture, vol 21, no. 12, pp. 3420-3433. 2022. Doi: https://doi.org/10.1016/j.jia.2022.08.056.; D. Rustia, L. Chiu, C. Lu, Y. Wu, S. Chen, J. Chung, J. Hsu, T. Lin, “Towards intelligent and integrated pest management through an AIoT-based monitoring system”, Pest. Manage. Sci., vol 78, no. 10, pp. 4288–4302, 2022. Doi: https://doi.org/10.1002/ps.7048.; I. Ahmad and K. Pothuganti, "Smart Field Monitoring using ToxTrac: A Cyber-Physical System Approach in Agriculture", 2020 International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India, pp. 723-727, 2020. Doi:10.1109/ICOSEC49089.2020.9215282.; S. Cecchi, S. Spinsante, A. Terenzi, S. Orcioni, “A Smart Sensor-Based Measurement System for Advanced Bee Hive Monitoring”, Sensors, vol 20, no. 2726, pp. 1-20, 2020. Doi: https://doi.org/10.3390/s20092726.; F. Murphy, M. Magno, P. Whelan and E. Vici, "b+WSN: Smart beehive for agriculture, environmental, and honey bee health monitoring — Preliminary results and analysis," 2015 IEEE Sensors Applications Symposium (SAS), Zadar, Croatia, pp. 1-6, 2020. Doi:10.1109/SAS.2015.7133587.; P. Saha, V. Kumar, S. Kathuria, A. Gehlot, V. Pachouri and A. S. Duggal, “Precision Agriculture Using Internet of Things and Wireless Sensor Networks”, 2023 International Conference on Disruptive Technologies (ICDT), Greater Noida, India, pp. 519-522, 2023. Doi:10.1109/ICDT57929.2023.10150678.; R. Singh, R. Berkvens and M. Weyn, “Energy Efficient Wireless Communication for IoT Enabled Greenhouses”, 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), Bengaluru, India, pp. 885-887, 2020. Doi:10.1109/COMSNETS48256.2020.9027392.; F. Kiani and A. Seyyedabbasi, “Wireless Sensor Network and Internet of Things in Precision Agriculture”, International Journal of Advanced Computer Science and Applications, vol 9, no. 6, pp. 99-103, 2018. Doi: http://dx.doi.org/10.14569/IJACSA.2018.090614.; O. Savale, A. Managave, D. Ambekar, S. Sathe, “Internet of Things in Precision Agriculture using Wireless Sensor Networks”, International Journal Of Advanced Engineering & Innovative Technology, vol 2, no. 3, pp. 1-4, Dec. 2015.; A. Sawant, J. Adinarayana and S. Durbha, “KrishiSense: A semantically aware web enabled wireless sensor network system for precision agriculture applications”, 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada, pp. 4090-4093, 2014. Doi:10.1109/IGARSS.2014.6947385.; C. Prakash, L. Singh, A. Gupta, S. Lohan, “Advancements in smart farming: A comprehensive review of IoT, wireless communication, sensors, and hardware for agricultural automation”, Sensors and Actuators A: Physical, vol 362, no. 114605, pp. 1- 25, 2023. Doi: https://doi.org/10.1016/j.sna.2023.114605.; H. Jawad, R. Nordin, S. Gharghan, A. Jawad, M. Ismail, “Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review”, Sensors, vol 17, no. 1781, pp. 1-4, 2017. Doi: https://doi.org/10.3390/s17081781.; E. Avşar, N. Mowla, “Wireless communication protocols in smart agriculture: A review on applications, challenges and future trends”, Ad Hoc Networks, vol 136, no. 102982, pp. 1- 25, 2022. Doi: https://doi.org/10.1016/j.adhoc.2022.102982.; V. Starčević, M. Simić, V. Risojević and Z. Babić, “Integrated video-based bee counting and multi-sensors platform for remote bee yard monitoring”, 21st International Symposium INFOTEH-JAHORINA (INFOTEH), East Sarajevo, Bosnia and Herzegovina, pp. 1-6, 2022. Doi:10.1109/INFOTEH53737.2022.9751284.; H. Remli, K. Wan, N. Ismail, A. González, J. Corchado, M. Mohamad, “Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review”, Sensors, vol 23, no. 7, pp. 1-22, 2023. Doi: https://doi.org/10.3390/s23073752.; S. Qazi, B. Khawaja and Q. U. Farooq, “IoT-Equipped and AI-Enabled Next Generation Smart Agriculture: A Critical Review, Current Challenges and Future Trends”, in IEEE Access, vol 10, pp. 21219-21235, 2022. Doi:10.1109/ACCESS.2022.3152544.; A. AlZubi and K. Galyna, “Artificial Intelligence and Internet of Things for Sustainable Farming and Smart Agriculture”, in IEEE Access, vol 11, pp. 78686-78692, 2023. Doi:10.1109/ACCESS.2023.3298215.; G. Sagar, B. Aastha, K. Laxman, “An introduction of fall armyworm (Spodoptera frugiperda) with management strategies: a review paper”, Nippon Journal of Environmental Science, vol 1, no. 1010, pp. 1-12, 2020. Doi: https://doi.org/10.46266/njes.1010.; C. Nicolas, B. Naila and R. Amar, “Energy efficient Firmware Over The Air Update for TinyML models in LoRaWAN agricultural networks”, 2022 32nd International Telecommunication Networks and Applications Conference (ITNAC), Wellington, New Zealand, pp. 21-27, 2022. Doi:10.1109/ITNAC55475.2022.9998338.; B. Miles, E. Bourennane, S. Boucherkha, S. Chikhi, “A study of LoRaWAN protocol performance for IoT applications in smart agriculture”, Computer Communications, vol. 164, pp. 148-157, 2020. Doi: https://doi.org/10.1016/j.comcom.2020.10.009.; D. Davcev, K. Mitreski, S. Trajkovic, V. Nikolovski and N. Koteli, “IoT agriculture system based on LoRaWAN”, 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy, pp. 1-4, 2018. Doi:10.1109/WFCS.2018.8402368.; J. Tovar, C. Pareja, O. García, L. Gutiérrez, “Performance evaluation of LoRa technology for implementation in rural areas”, Dyna, vol 88, no. 216, pp. 69-78, Feb. 2021. Doi:10.15446/dyna.v88n216.88258.; P. Supanirattisai, K. Pimpin, W. Srituravanich and N. Damrongplasit, “Smart Agriculture Monitoring and Management System using IoT-enabled Devices based on LoRaWAN”, 2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC), Phuket, Thailand, pp. 679-682, 2022. Doi:10.1109/ITCCSCC55581.2022.9894956.; Y.M. Bar-On, R. Phillips, R. Milo, “The biomass distribution on earth”, Proc. Natl. Acad. Sci. U. S. A. 115, 6506–6511. 2018. https://doi.org/10.1073/pnas.1711842115; A. P. Genoud, J. Torsiello, M. Belson y B.P. Thomas, “Entomological photonic sensors: Estimating insect population density, its uncertainty and temporal resolution from transit data”, Ecological Informatics, 61, 101186, 2021. https://doi.org/10.1016/j.ecoinf.2020.101186; Murciaplaza, 2021. [En línea]. Disponible en https://murciaplaza.com/plagasenfermedades-cultivos-region-provocaron-120-millones-perdidas-2020.; N. Ardila, EL TIEMPO. 2020. [En línea]. Disponible en https://www.eltiempo.com/colombia/otras-ciudades/plaga-de-langostas-cultivosarrasados-en-los-llanos-orientales-por-una-plaga-noticias-hoy-518744; M. Huerga y S. San Juan, “El control de las plagas en la agricultura argentina. Estudio sectorial Agrícola Rural Banco Mundial/Centro de inversiones FAO”, Argentina. 2005; M. Vargas y D. Alvear, “Agricultura limpia: manejo racional de plaguicidas para control de plagas en invernaderos” [en línea]. Disponible en https://biblioteca.inia.cl/handle/123456789/6089; G. A. Holguin, B. L. Lehman, L. A. Hull, V. P. Jones y J. Park, “Electronic traps for automated monitoring of insect populations”. IFAC Proceedings Volumes, 43(26), 49- 54. 2010. https://doi.org/10.3182/20101206-3-JP-3009.00008; I. Rigakis, K. Varikou, A. Nikolakakis, Z. Skarakis, N. Tatlas y I. Potamitis, “The e-funnel trap: Automatic monitoring of lepidoptera; a case study of tomato leaf miner”. Computers and Electronics in Agriculture, 185, 106154. 2021, https://doi.org/10.1016/j.compag.2021.106154; I. Potamitis, I. Rigakis, N. Vidakis, M. Petousis y M. Weber, “Affordable Bimodal Optical Sensors to Spread the Use of Automated Insect Monitoring”. J. Sens. 2018. Article ID 3949415: https://doi.org/10.1155/2018/3949415; M. Weber, M. Geier, I. Potamitis, C. Pruszynski, M. Doyle, A. Rose, M. Geismar y J. Encarnacao. “The BG-counter, the first operative automatic mosquito counting device for online mosquito monitoring: field tests and technical outlook”. AMCA 2017 83rd Annual Meeting, 2017, pp 57.; M. Preti, F. Verheggen, S. Angeli, “Insect pest monitoring with camera-equipped traps: strengths and limitations”. J. Pest. Sci. 2020. https://doi.org/10.1007/s10340-020- 01309-4; N. Flórián, L. Gránicz, V. Gergócs, F. Tóth, M. Dombos, M. “Detecting Soil Microarthropods with a Camera-Supported Trap”. Insects. 11 (244) 2020. https://doi.org/10.3390/insects11040244; A. Gutierrez, A. Ansuategi, L. Susperregi, C. Tubío, I. Ranki ́c, L. Lenˇza, “Benchmarking of Learning Strategies for Pest Detection and Identification on Tomato Plants for Autonomous Scouting Robots Using Internal Databases”. J. Sens. 1–15. 2019, https://doi.org/10.1155/2019/5219471; E. Goldshtein, Y. Cohen, A. Hetzroni, Y. Gazit, D. Timar, L. Rosenfeld y A. Mizrach, “Development of an automatic monitoring trap for Mediterranean fruit fly (Ceratitis capitata) to optimize control applications frequency”. Computers and Electronics in Agriculture, 139, 115-125, 2017. https://doi.org/10.1016/j.compag.2017.04.022; B. Keswani, A. Mohapatra, A. Mohanty, A. Khanna, J. Rodriguez, D. Gupta, V. De Albuquerque, “Adapting weather conditions based IoT enabled smart irrigation technique in precision agriculture mechanisms”. Neural Comput. Appl. 31: 277–292, 2019. https://doi.org/10.1007/s00521-018-3737-1; L. García, L. Parra, J.M. Jimenez, J. Lloret, P. Lorenz, “IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture”. Sensors, 20(4),1042, 2020, https://doi.org/10.3390/s20041042; F.A. Paredes-Sánchez, G. Rivera, V. Bocanegra-García, H. Y. Martínez-Padrón, M. Berrones-Morales, N. Niño-García y V. Herrera-Mayorga. “Advances in control strategies against Spodoptera Frugiperda. A review”. Molecules, 26(18), 5587, 2021. https://doi.org/10.3390/molecules26185587; Ecobertura., Spodoptera frugiperda (Smith) 2023. [En línea]. Disponible en https://ecobertura.es/spodoptera-frugiperda/; Weather Spark., 2023. Average Weather in Villavicencio, Colombia. [En línea]. Disponible en https://weatherspark.com/y/24273/Average-Weather-in-VillavicencioColombia-Year-Round; S. A. Vaca Vargas, “Automated greenhouse, instrumentation and fuzzy logic”, Visión Electrónica, vol. 14, no. 1, pp. 119–127, ene. 2020. https://doi.org/10.14483/22484728.15907; A. M. Molano-Gómez; A. F. Neira-Reyes; L. H. Correa-Salazar; E. Bernal-Alzate, “Topological alternatives for photovoltaic integration in rural areas”, Visión electrónica, vol. 13, no. 1, januaryjune 2019, pp. 24-32.; Wohlers, T. (2020). "Wohlers Report 2020: 3D Printing and Additive Manufacturing State of the Industry." Wohlers Associates, Inc.; McKinsey & Company. (2018). "The next frontiers for additive manufacturing." McKinsey Digital.; Stockholm Environment Institute, J. A. Vega Araújo, M. Muñoz Cabré, y Stockholm Environment Institute, «Energía solar y eólica en Colombia: panorama y resumen de políticas 2022», Stockholm Environment Institute, mar. 2023. doi:10.51414/sei2023.016.; Wohlers, T. (2019). "Wohlers Report 2019: 3D Printing and Additive Manufacturing State of the Industry." Wohlers Associates, Inc.; Chua, C. K., Leong, K. F., & Lim, C. S. (2014). "Rapid Prototyping: Principles and Applications." World Scientific Publishing Company.; Kruth, J. P., Leu, M. C., & Nakagawa, T. (2003). "Progress in additive manufacturing and rapid prototyping." CIRP Annals - Manufacturing Technology, 52(2), 525-540.; Gibson, I., Rosen, D. W., & Stucker, B. (2015). "Additive Manufacturing Technologies: 3D Printing, Rapid Prototyping, and Direct Digital Manufacturing." Springer.; Cooper, R. G. (2019). "Product Leadership: Pathways to Profitable Innovation." Basic Books.; Ulrich, K. T., & Eppinger, S. D. (2015). "Product Design and Development." McGraw-Hill Education.; L. L. Hurtado-Cortés, J. A. Forero-Casallas, y V. E. Ruiz-Rosas, “Tecnologías automatizadas implementadas en la FMS HAS200”, Visión Electrónica, vol. 16, no. 1, jun. 2022.; McGrath, R. G. (2020). "Seeing Around Corners: How to Spot Inflection Points in Business Before They Happen." Houghton Mifflin Harcourt.; H. Beltrán-Cicery, D. Rojas-Sarmiento, y F. Barrera-Prieto, “Implementation of a manufacturing cell in assembly of Hanoi tower”, Visión Electrónica, vol. 16, no. 2, sep. 2022.; A. L. Vargas, "El profesional de mercadeo en tiempos de Inteligencia Artificial," IBM Colombia, 2017. [Online]. Available: https://www.revistapym.com.co/articulos/mercadeo/10851/el-profesional-de-mercadeo-entiempos-de-inteligencia-artificial.; C. F. Villa Gómez, "Mercadeo e Inteligencia Artificial," La República, 2020. [Online]. Available: https://www.larepublica.co/analisis/carlos-fernando-villa-gomez-400403/mercadeoe-inteligencia-artificial-3048716.; "Con el impulso de la Inteligencia Artificial, Colombia podría triplicar su productividad y aumentar su PIB hasta un 6.8%," Microsoft Noticias, 2019. [Online]. Available: https://news.microsoft.com/es-xl/con-el-impulso-de-la-inteligencia-artificial-colombia-podriatriplicar-su-productividad-y-aumentar-su-pib-hasta-un-6-8/; H. Wong, "Avances y Problemas en la Inteligencia Artificial de Colombia 2022," LinkedIn, 2022. [Online]. Available: https://es.linkedin.com/pulse/avances-y-problemas-en-lainteligencia-artificial-de-colombia-wong.; "IA y ChatGPT transformarán las prácticas de mercadeo," Portafolio, 2023. [Online]. Available: https://www.portafolio.co/tendencias/ia-y-chatgpt-transformaran-las-practicas-demercadeo-577916.; P. T. Hernández, "El Marco Ético para la Inteligencia Artificial en Colombia: una oportunidad para implementar proyectos de IA que beneficien a toda la ciudadanía," 2022. [Online]. Available: https://www.ccit.org.co/articulos-tictac/el-marco-etico-para-la-inteligencia-artificialen-colombia-una-oportunidad-para-implementar-proyectos-de-ia-que-beneficien-a-toda-laciudadania/.; "Inteligencia artificial: definición, historia, usos, peligros," DataScientest, 2023. [Online]. Available: https://datascientest.com/es/inteligencia-artificial-definicion.; A. Flores, "Conoce la historia del marketing digital y su evolución hasta el día de hoy," Crehana, 2021. [Online]. Available: https://www.crehana.com/blog/transformaciondigital/historia-del-marketing-digital/.; "Evolución del internet y mercadotecnia digital," Preceden, 2023. [Online]. Available: https://www.preceden.com/timelines/841917-evoluci-n-del-internet-y-mercadotecnia-digital.; "Colombia se adhiere a acuerdo sobre Inteligencia Artificial ante los países de la OCDE," Mintic, 2019. [Online]. Available: https://www.ccb.org.co/Clusteres/Cluster-de-Software-yTI/Noticias/2019/Mayo-2019/Colombia-se-adhiere-a-acuerdo-sobre-Inteligencia-Artificialante-los-paises-de-la-OCDE.; A. de Ignacio, "La Inteligencia Artificial en el marketing digital," 2023. [Online]. Available: https://www.cyberclick.es/numerical-blog/la-inteligencia-artificial-en-el-marketing-digital.; Meisam Mahdavi, Mohammad S. Javadi, João P.S. Catalão, Integrated generationtransmission expansion planning considering power system reliability and optimal maintenance activities, International Journal of Electrical Power & Energy Systems, Volume 145, 2023, 108688, ISSN 0142- 0615,https://doi.org/10.1016/j.ijepes.2022.108688. (https://www.sciencedirect.com/science/article/pii/S0142061522006846); Long Ding, Hong Wang, Kai Kang, Kai Wang, A novel method for SIL verification based on system degradation using reliability block diagram, Reliability Engineering & System Safety, Volume 132, 2014, Pages 36-45, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2014.07.005. (https://www.sciencedirect.com/science/article/pii/S0951832014001604); ISO 55001:2014 Asset Management. Management systems – RequirementsThe British Standards Institution. 2014.; B. Dhilon, “Applied Reliability and Quality Fundamentals, Methods and Procedures, New Jersey: Springer, 2007.; Mohsen Firouzi, Abouzar Samimi, Abolfazl Salami, Reliability evaluation of a composite power system in the presence of renewable generations, Reliability Engineering & System Safety, Volume 222, 2022, 108396, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2022.108396. (https://www.sciencedirect.com/science/article/pii/S0951832022000710); R. Yajun and M. Xiurui, "The reliability evaluation of the power system containing wind farm using the improved state space partition method," 2014 International Conference on Power System Technology, Chengdu, China, 2014, pp. 36-41, doi:10.1109/POWERCON.2014.6993498.; S. Anbazhagan, N. Kumarappan, Day-ahead deregulated electricity market price forecasting using neural network input featured by DCT, Energy Conversion and Management, Volume 78, 2014, Pages 711-719, ISSN 0196-8904, https://doi.org/10.1016/j.enconman.2013.11.031.; Xudong Fan, Xijin Zhang, Xiong Bill Yu, Uncertainty quantification of a deep learning model for failure rate prediction of water distribution networks, Reliability Engineering & System Safety, Volume 236, 2023,109088, ISSN 0951-8320, https://doi.org/10.1016/j.ress.2023.109088. (https://www.sciencedirect.com/science/article/pii/S0951832023000030); Wei Qiu, Qiu Tang, Zhaosheng Teng, Wenxuan Yao, Jun Qiu, Failure rate prediction of electrical meters based on weighted hierarchical Bayesian,Measurement, Volume 142, 2019, Pages 21-29, ISSN 0263-2241, https://doi.org/10.1016/j.measurement.2019.04.062. (https://www.sciencedirect.com/science/article/pii/S026322411930380X; C.Ramírez, “Phyton para finanzas CURSO PRÁCTICO”, Bogotá: Ediciones de la U, pp.223-233,2021.; C.Ramírez, “Phyton para finanzas CURSO PRÁCTICO”, Bogotá: Ediciones de la U, pp.279-311,2021.; J. Stock, “Introducción a la econometría”, Madrid: Pearson educación S.A, pp.373- 411, 2012.; G. Box, “Time Series Analysis Forecasting and Control”, New Jersey: John Wiley & Sons Ltd, pp. 2-43, 2016.; S. Raschka, “Machine Learning con PyTorch y Scikit-Learn”, Madrid: Alphaeditorial, pp.290-307, 2023.; Yanhui CHEN, Mengmeng Ma, Yuye Zou, Forecasting hourly electricity demand with nonparametric functional data analysis,Procedia Computer Science, Volume 214, 2022, Pages 428-436, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2022.11.195. (https://www.sciencedirect.com/science/article/pii/S1877050922019056); Ye Zhu, Shiwen Xie, Yongfang Xie, Xiaofang Chen, Temperature prediction of aluminum reduction cell based on integration of dual attention LSTM for non-stationary subsequence and ARMA for stationary sub-sequences, Control Engineering Practice, Volume 138, 2023,105567, ISSN 0967-0661, https://doi.org/10.1016/j.conengprac.2023.105567. (https://www.sciencedirect.com/science/article/pii/S0967066123001363); Shao, Y., Zhang, D., Chu, H., Zhang, X., & Rao, Y. (2021). A Review of YOLO Object Detection Based on Deep Learning.; Bhasin, S. (2019). Real-time Object Detection with YOLO, OpenCV and Python.; Suresh et al. (2020). Object Detection with YOLO for Intelligent Traffic Monitoring System.; Liu, Y., Shi, Q., Guo, W., & Liao, W. (2020). A Real-time, Mobile-object Detection Approach for Unmanned Aerial Vehicle Based Forest Fire Surveillance System.; Jiang, P., Ergu, D., Liu, F., Cai, Y., & Ma, B. (2022). A Review of YOLO Algorithm Developments.; Mauro Tucci, A. B. (s/f). "YOLO-S: A Lightweight and Accurate YOLO-like Network for Small Target Selection in Aerial Imagery".; Sharma, A., Pathak, J., Prakash, M., & Singh, J. N. (2020). Object Detection using OpenCV and Python. International Journal of Innovative Research in Computer and Communication Engineering, 8(6), 2736-2741.; “Procesamiento de Imágenes y Visión Artificial con MATLAB Video,” Mathworks.com, 2021. https://la.mathworks.com/videos/image-processing-and-computer-vision-with-matlab1597884648964.html (accessed Jul. 25, 2023).; Ricardo Alirio Gonzalez, R. Ferro, and Daríoo Liberona, “Government and governance in intelligent cities, smart transportation study case in Bogotá Colombia,” vol. 11, no. 1, pp. 25– 34, Mar. 2020, doi: https://doi.org/10.1016/j.asej.2019.05.002.; Beatriz Elena Pineda, Claudia Helena Muñoz, & Gil, H. (2018). Aspectos relevantes de la movilidad y su relación con el medio ambiente en el Valle de Aburrá: una revisión. Ingeniería Y Desarrollo, 36(2), 489–508. https://www.redalyc.org/journal/852/85259689013/html/; IA por el Planeta: Destacando las innovaciones de IA para la movilidad sostenible y las ciudades inteligentes. (2023). Unesco.org. https://www.unesco.org/es/articles/ia-por-elplaneta-destacando-las-innovaciones-de-ia-para-la-movilidad-sostenible-y-las-ciudades; Gómez Zapata, C. A. (2019). Reconocimiento de objetos del hogar, usando redes neuronales convolucionales para personas con discapacidad visual. Revista Científica de Ingeniería y Tecnología, 2(2), 1-10. https://dialnet.unirioja.es/descarga/articulo/7436051.pdf.; Olabe, X. B. (s/f). REDES NEURONALES ARTIFICIALES Y SUS APLICACIONES. Ehu.eus. Recuperado el 8 de julio de 2023, de URL: https://ocw.ehu.eus/pluginfile.php/40137/mod_resource/content/1/redes_neuro/contenidos/pd f/libro-del-curso.pdf; Murgui, J., & García-Sánchez, A. J. (2018). Clasificación y reconocimiento de imágenes con redes neuronales para aplicaciones industriales. URL: https://riunet.upv.es/bitstream/handle/10251/115464/Murgui.pdf?sequence=1; Ortiz, G., & Sánchez, A. I. (2020). Emprendimiento y tecnologías de la información y la comunicación en Bogotá. Cuadernos de Administración, 36(67), 199-211.; Torres, J., & Acosta, H. (2019). La innovación en el ecosistema emprendedor de Bogotá. Cuadernos de Administración, 35(64), 251-262.; Uribe, F., & Guzmán, J. (2021). La colaboración público-privada en el fomento de la innovación en Bogotá: el caso de la identificación de objetos en el contexto vial. Revista Internacional de Gestión y Economía Aplicada, 11(1), 89-101.; Centro de Investigación de la Universidad Distrital Francisco José de Caldas. (2023). Udistrital.edu.co. https://revistas.udistrital.edu.co/index.php/visele/article/view/18942/18701; Chiroma, R. C. U. (2021). Vehicle detection, counting, and classification in traffic videos: A survey. IEEE Transactions on Intelligent Transportation Systems, 22(10), 3773-3785. [20] Rao, S. S. (2018). Vehicle detection and identification using computer vision and deep learning techniques. IEEE Transactions on Intelligent Transportation Systems, 19(10), 2827- 2836.; Akhand, M. A. H. (2019). Vehicle Recognition from License Plate Number using Deep Learning. arXiv preprint arXiv:1903.09203.; Sandra Milena García Ávila, Cristian Alexander Vega Camacho, José Vicente Cadena López, Ricardo Alirio González Bustamante, Paola Andrea Mateus Abaunza. (2021). Diseño y aplicación de una herramienta para identificar y clasificar motocicletas mediante una red neuronal convolucional. researchgate.net. URL: https://doi.org/ISBN:978-958-53278-6-3; valentynsichkar, “Traffic Signs Detection by YOLO v3, OpenCV, Keras,” Kaggle.com, Apr. 15, 2022. https://www.kaggle.com/code/valentynsichkar/traffic-signs-detection-by-yolo-v3- opencv-keras (accessed Jul. 25, 2023).; Motor Colombia. (2022, February 23). 7.270 muertos en accidentes de tránsito en 2021. Motor Colombia; Motor Colombia. URL: https://www.motor.com.co/industria/7.270-muertos-enaccidentes-de-transito-en-2021-20220124-0001.html; R. Jiménez Moreno, O. Avilés, y D. M. Ovalle, “Red neuronal convolucional para discriminar herramientas en robótica asistencial”, Vis. Electron., vol. 12, no. 2, pp. 208–214, oct. 2018. https://doi.org/10.14483/22484728.13996; L. L. Hurtado-Cortés y J. A. Forero-Casallas, “Identification and fault detection in actuator using NN-NARX”, Vis. Electron., vol. 2, no. 2, pp. 304–312, dic. 2019. https://doi.org/10.14483/22484728.18432; Propia. (2023). Fragmento del conjunto de imágenes de entrenamiento para YOLO [Figura].; Propia. (2023). Matriz de confusión de una capacitación sobre imágenes de Camiones. [Figura].; Propia. (2023). Curva de precisión-confianza para el entrenamiento de imágenes de Camiones. [Figura].; Propia. (2023). Salida "Results.png" sobre el entrenamiento de imágenes de Camiones. [Figura].; Propia. (2023). Salida "Train.png" sobre el entrenamiento de imágenes de Camiones. [Figura].; Propia. (2023). Salida "Val.png" sobre el entrenamiento para Camiones. [Figura]; Propia. (2023). Salida de los gráficos de correlación de etiquetas para el entrenamiento de imágenes de Camiones. [Figura].; Propia. (2023). Esquema de entrenamiento general utilizado para el reconocimiento de imágenes con YOLO. [Figura]; Anagnoste, Sorin. "Robotic Automation Process – The operating system for the digital enterprise" Proceedings of the International Conference on Business Excellence, vol.12, no.1, 2018, pp.54-69. https://doi.org/10.2478/picbe-2018-0007; C. T. Kaya, M. Turkyilmaz, & B. Birol, “Impact of RPA Technologies on Accounting Systems”. Muhasebe ve Finansman Dergisi, pp. 235–250, Apr. 2019, https://doi.org/10.25095/mufad.536083; Morgan.O’ Mara., “How Much Paper is Used in One Day”, Record Nations, blog. https://www.recordnations.com/blog/how-much-paper-is-used-in-one-day/; Thomas Teunissen. Success factors for RPA application in small and medium sized enterprises. University of Twente. From https://essay.utwente.nl/77592/1/Teunissen_BA_EEMCS.pdf; James Barlow. 2023. OCRmyPDF documentation. Read the Docs. From: https://ocrmypdf.readthedocs.io/en/latest/index.html; T Malathi, et al. 2021. An Experimental Performance Analysis on Robotics Process Automation (RPA) With Open Source OCR Engines: Microsoft Ocr And Google Tesseract OCR. IOP Conf. Ser.: Mater. Sci. Eng. 1059 012004. https://doi.org/10.1088/1757-899X/1059/1/012004; Arkadiusz Januszewski et al. 2021. Benefits of and Obstacles to RPA Implementation in Accounting Firms. Procedia Computer Science 192 (2021). 4672–4680. https://doi.org/10.1016/j.procs.2021.09.245; Madakam, Somayya, Holmukhe, Rajesh M., and Jaiswal, Durgesh Kumar. (2019). The Future Digital Work Force: Robotic Process Automation (RPA). JISTEM - Journal of Information Systems and Technology Managements, 16, e201916001.https://doi.org/10.4301/S1807-1775201916001; Ribeiro, J., Lima, R., Paiva, S. (2021). Document Classification in Robotic Process Automation Using Artificial Intelligence—A Preliminary Literature Review. In: Sharma, H., Gupta, M.K., Tomar, G.S., Lipo, W. (eds) Communication and Intelligent Systems. Lecture Notes in Networks and Systems, vol 204. Springer, Singapore. https://doi.org/10.1007/978-981-16-1089-9_18; Leslie Willcocks, John Hindle & Mary Lacity. 2019. Keys to RPA Success - Executive Research Report. Knowledge Capital Partners. From: https://engineering.report/Resources/Whitepapers/9a46b779-a4a1-4188-8a1deb769ba4fbb1_Keys-RPA-Success.pdf; J. C. Diaz, D. Zunino, y G. Nicolino, “Análisis de la extracción de datos personales sin autorización de un dispositivo IoT”, Visión Electrónica, vol. 16, no. 2, dic. 2022.; S. Scheuber, and M. Vanhoy, "Emotional and Neurological Responses to Timbre in Electric Guitar and Voice," Paper 10505, (2021 May.).; J. Stanhope, and P. Weinstein, “The human health effects of singing bowls: A systematic review”, Complementary therapies in medicine, 51, 102412, (2020 Apr.).; C. J. Bless, “Análisis de la actividad EEG durante una sesión de estimulación multisensorial en una sala Snoezelen”, Universidad de Valladolid. Escuela Técnica Superior de Ingenieros de Telecomunicación, 2020.; L. Gong, M. Li, T. Zhang, W. Chen, “EEG emotion recognition using attention-based convolutional transformer neural network”, Biomedical Signal Processing and Control, Vol. 84, 2023.; C. Zeng, W. Lin, N. Li, Y. Wen, Y. Wang, W. Jiang, J. Zhang, H. Zhong, X. Chen, W. Luo, et al. “Electroencephalography (EEG)-Based Neural Emotional Response to the Vegetation Density and Integrated Sound Environment in a Green Space”, Forests, 2021.; S. N. Safder, M. U. Akram, M. N. Dar, A. A. Khan, S. G. Khawaja, A. R. Subhani, I. K. Niazi, S. Gul, “Analysis of EEG signals using deep learning to highlight effects of vibration-based therapy on brain”, Biomedical Signal Processing and Control, Vol. 83, 2023.; A. E. Nieto-Vallejo, O. F. Ramírez-Pérez, L. E. Ballesteros-Arroyave, and A. Aragón, “Design of a Neurofeedback Training System for Meditation Based on EEG Technology”, Revista Facultad de Ingeniería, 30(55), 2021; H.Y. Huang & P.C. Lo (2019) EEG dynamics of experienced Zen meditation practitioners probed by complexity index and spectral measure, Journal of Medical Engineering & Technology, 33:4, 314-321, DOI:10.1080/03091900802602677.; F. Ramos-Argüelles, G. Morales, S. Egozcue, R.M. Pabón, M.T. Alonso, “Técnicas básicas de electroencefalografía: principios y aplicaciones clínicas”, vol. 32, 2009.; J. Zain, “El uso de cuencos tibetanos como recurso vibroacústico en Musicoterapia Receptiva”, XVIII Forum estadual de Musicoterapia, 2012.; A. Ramírez Sánchez, C. Espinosa Calderón, A. F. Herrera Montenegro, E. Espinosa Calderón, A. Ramírez Moyano, “Beneficios de la psicoeducación de entrenamiento en técnicas de relajación en pacientes con ansiedad”, Revista Enfermería Docente, 2014.; M. Tobal, “Actividad Cerebral y Deporte: Un Estudio Mediante Mapas de Actividad Eléctrica Cerebral”, Universidad Complutense de Madrid, 1992.; EMOTIV. (2023, 6 abril). EMOTIV Insight 2 with 5 Channel EEG Headset %7C EMOTIV. https://www.emotiv.com/product/emotiv-insight-5-channel-mobile-brainwear/.; Sánchez, M. A. C. Lozano, M. S. G. (2016). El sonido que sana: Manual práctico de sanación a través del sonido. LA ESFERA DE LOS LIBROS, S.L.; Singing Bowl Tones and Frequencies: Complete Guide (2022). (s. f.). Shanti Bowl. https://www.shantibowl.com/blogs/blog/singing-bowl-tones-and-frequencies-complete-guide; Torrades, S. (2007, 1 noviembre). Estrés y burn out. Definición y prevención %7C Offarm. de:https://www.elsevier.es/es-revista-offarm-4-articulo-estres-burn-out-definicion-prevencion13112896; Domingues Hirsch, C., Devos Barlem, E. L., De Almeida, L. K., Tomaschewski Barlem, J. G., Lerch Lunardi, V., & Marcelino Ramos, A. (2018). Stress triggers in the educational environment from the perspective of nursing students. Texto & Contexto Enfermagem, 27(1), e0370014.; Zárate Depraect, N. E., Soto Decuir, M. G., Castro Castro, M. L., & Quintero Salazar, J. R. (2017). Estrés académico en estudiantes universitarios: Medidas preventivas. Revista de Alta Tecnología y la Sociedad, 9(4), 92-98.; Barlett. (1991). Stereo Microphone Techniques. Stoneham, Massachusetts: Reed Publishing (USA).; Holman, T. (2008). Sourround Sound: Up And Running. Burlington, Massachusets: Elsevier Inc.; Howard, D., & Angus, J. (2000). Acoustics and Psychoacoustics (2nd ed.). Routledge. https://doi.org/10.4324/9780080498522.; Burrough, P. A., & McDonnell, R. A. (1998). Principles of geographical information systems (2a ed.). Clarendon Press.; D. S. Garzón-Ramírez, M. S. Sanabria-Guio, y J. D. Cely-Fajardo, “Geolocation system and vehicular analysis for motorcyclists”, Vis. Electron., vol. 2, no. 1, pp. 95–106, mar. 2019. https://doi.org/10.14483/22484728.18416; Home. (2022, abril 15). Open Geospatial Consortium. https://www.ogc.org; Google. (s/f-b). Google.com. Recuperado el 31 de agosto de 2023, de https://earth.google.com/; Documentation. (s/f). Qgis.org. Recuperado el 15 de septiembre de 2023, de https://www.qgis.org/en/docs/index.html; GDAL — GDAL documentation. (s/f). Gdal.org. Recuperado el 15 de septiembre de 2023, de https://gdal.org/; GIS mapping software, location intelligence & spatial analytics. (s/f). Esri.com. Recuperado el 15 de septiembre de 2023, de https://www.esri.com/enus/home; P. F. Martín-Gómez, J. E. Rangel-Díaz, J. O. Montoya-Gómez, y J. L. RubianoFernández, “Automation of greenhouse pesticide application: design and construction”, Visión Electrónica, vol. 2, no. 1, pp. 129–133, mar. 2019. https://doi.org/10.14483/22484728.18419; F. A. Molina-Guzmán, S. A. Torres-Castillo, G. A. López-Martínez, “Use of wastewater and waste from Colombian pacific for electrical generation”, Visión Electrónica, vol. 16, no. 1, 2022.; B. Smith, A., & Johnson, “Automated Fruit Classification for Quality Control,” J. Agric. Technol., vol. 10, no. 4, pp. 1015–1027, 2018.; C. G. Peñaranda, “ANÁLISIS DE COSTOS DE LA PRODUCCIÓN DE DURAZNO (PRUNUS PÉRSICA) EN LA PROVINCIA DE PAMPLONA (NORTE DE SANTANDER),” Rev. la Fac. Ciencias Económicas y Empres., pp. 145–162, 2012.; 2. Camara de Comercio de Medellín, “HERRAMIENTAS EMPRESARIALESAUTOMATIZACIÓN DE LOS PROCESOS INDUSTRIALES,” 2018. http://herramientas.camaramedellin.com.co/Inicio/Buenaspracticasempresariales/Bibliot ecaProduccónyOperaciones/Automatizaciondelosprocesosindustriales.aspx.; C. García, A. López, and F. Fernández, “Deep Learning-Based Fruit Recognition and Classification System for Precision Agriculture,” Comput. Electron. Agric., vol. 180, p. 105832, 2020.; R. Patel, A. Sharma, and S. Kumar, “Real-time Fruit Recognition and Grading System for Robotic Harvesting,” Comput. Electron. Agric., vol. 157, pp. 306–316, 2019.; M. Megajothi, C. Meenakshi, and R. Rajakumari, “Automation of Fruit Quality Analysis System,” in 2nd International Conference on Applied Soft Computing Techniques C., 2022, pp. 424–425.; W. M. Syahrir, A. Suryanti, and C. Connsynn, “Color grading in Tomato Maturity Estimator using image processing technique,” in 2009 2nd IEEE International Conference on Computer Science and Information Technology, 2009, pp. 276–280, doi:10.1109/ICCSIT.2009.5234497.; Z. Ma, J.-H. Xue, A. Leijon, Z.-H. Tan, Z. Yang, and J. Guo, “Decorrelation of Neutral Vector Variables: Theory and Applications,” IEEE Trans. Neural Networks Learn. Syst., vol. 29, no. 1, pp. 129–143, 2018, doi:10.1109/TNNLS.2016.2616445.; L. Zhang, J. Jia, G. Gui, X. Hao, W. Gao, and M. Wang, “Deep Learning Based Improved Classification System for Designing Tomato Harvesting Robot,” IEEE Access, vol. 6, pp. 67940–67950, 2018, doi:10.1109/ACCESS.2018.2879324.; J. Chen, Z. Liu, H. Wang, A. Núñez, and Z. Han, “Automatic defect detection of fasteners on the catenary support device using deep convolutional neural network,” IEEE Trans. Instrum. Meas, vol. 67, no. 2, pp. 257–269, 2018.; H. Yu, Z.-H. Tan, Z. Ma, R. Martin, and J. Guo, “Spoofing detection in automatic speaker verification systems using DNN classifiers and dynamic acoustic features,” IEEE Trans. Neural Netw. Learn. Syst., vol. 29, no. 10, pp. 4633–4644, 2018.; and Y. A. X. Sun, G. Gui, Y. Li, R. P. Liu, “A novel deep neural network with feature reuse for Internet of Things,” IEEE Internet Things.; B. S and U. J, “Deep fruit detection in orchards,” IEEE Int. Conf. Robot. Autom, no. May, pp. 3626–3633, 2017.; Vanguardia, “¿Como Puede la inteligencia artificial mejorar nuestras vidas?,” 2016. http://www.lavanguardia.com/vida/20161218/412710361329/como-puede-lainteligencia-artificial-mejorar-nuestras-vidas.html.; C. Oehninger, “El Impacto de la Robótica y la Automatización del Empleo en Uruguay,” 2018.; R. Terminio and E. Rimbau-Gilabert, “La digitalización del entorno de trabajo: la llegada de la robótica, la automatización y la inteligencia artificial (RAIA) desde el punto de vista de los Informal learning and work View project Creative industry network of entrepreneurs-CINet View project,” no. May, 2018, [Online]. Available: https://www.researchgate.net/publication/325059719.; D. BROUGHAM and J. HAAR, “Employee assessment of their technological redundancy,” Labour y Ind., 2017.; McKinsey And Company, “UN FUTURO QUE FUNCIONA: AUTOMATIZACIÓN, EMPLEO Y PRODUCTIVIDAD,” New York, 2017. doi:10.1787/agr_outlook-2017-3-es; Agua Libre. "Lo que necesitas saber sobre la Telemetría," 2021. Disponible en: https://agualibre.cl/telemetria-2/; D. J. Cardoso Ortegón and J. D. Ramírez Tovar, "Propuesta de un sistema de potabilización de aguas subterráneas, caso de estudio pozo finca el arbolito-ubicado en la vereda Caimanera en el municipio de el Espinal - Tolima teniendo en cuenta la caracterización física, química y microbiológica," Proyecto de grado, Universidad Piloto de Colombia, 2021. Disponible en: http://repository.unipiloto.edu.co/handle/20.500.12277/10116.; A. Jiménez, F. Velásquez, y S. Puente, “Sistema inteligente de prescripción de riego agrícola basado en redes de sensores y modelado de cultivos”, Visión Electrónica, vol. 17, no. 1, feb. 2023.; Digital Senses. "Telemetría y Monitoreo efectivo de Pozos de Agua," Disponible en: https://www.digitalsenses.io/medidores-de-pozos-de-agua/; E. M. González-Clavijo, J. C. Contreras-Niño, y H. J. Eslava-Blanco, “Automatización del vivero Semigar”, Visión Electrónica, vol. 16, no. 1, jun. 2022.; Integra Instrumentación. "Instalación de telemetría para pozos," Disponible en: https://integrainstrumentacion.cl/instalacion-de-telemetria-para-pozos/; F. C. Castañeda-Árias y K. S. Novoa-Roldan, “Remote crops: case study of critical variables”, Visión. Electrónica, vol. 16, no. 1, ene. 2022.; Nettra. "Monitoreo de pozos de extracción de agua subterránea," Disponible en: https://nettra.tech/monitoreo-de-pozos-de-extraccion-de-agua-subterranea/; B. Böttcher, J. Badinger, N. Moriz, and O. Niggemann, “Design of industrial automation systems — Formal requirements in the engineering process,” in 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), 2013, pp. 1–4. doi:10.1109/ETFA.2013.6648148.; N. Papakonstantinou, J. Karttunen, S. Sierla, and V. Vyatkin, “Design to automation continuum for industrial processes: ISO 15926 – IEC 61131 versus an industrial case,” in 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2019, pp. 1207–1212. doi:10.1109/ETFA.2019.8869325.; J. E. Martinez Baquero, “Diseño y construcción de equipo automatizado para separar mezclas,” Visión Electrónica Más que un estado sólido, vol. 8, no. 2, pp. 87–93, 2014, [Online]. Available: https://revistas.udistrital.edu.co/index.php/visele/article/view/9880; M. A. Monzón Herrera, “Diseño de un sistema dedicado al monitoreo y automatización de parámetros de proceso en una línea de producción de cartones moldeados (Doctoral dissertation).,” Universidad de San Carlos de Guatemala, 2019.; C. M. Bustamante Álvarez, J. E. Martínez Baquero, and C. Torres Gómez, “SCADA System of Physicochemical Variables in a Mixture Separator,” Rev. Inge CUC, vol. 11, no. 1, pp. 85–98, 2015, doi:10.17981/ingecuc.11.1.2015.09.; F. G. Astudillo, “Diseño y simulación de un control automático para una cámara de fermentación de pan por medio de un automáta programable,” ESCUELA POLITÉCNICA NACIONAL, 2010. [Online]. Available: https://bibdigital.epn.edu.ec/handle/15000/2231; P. A. Quinteros, M. C. Zurita, N. C. Zambrano, and L. M. Esthela, “Automatización de los procesos industriales,” J. Bus. Entrep. Stud., vol. 4, no. 2, pp. 123–131, 2020, [Online]. Available: https://dialnet.unirioja.es/servlet/articulo?codigo=7888290; F. F. Cando Herrera and G. F. Medina Lescano, “Implementación de un sistema de control y monitoreo de nivel de agua para el sistema de riego Chambo –Guano en la provincia de Chimborazo,” 2021, [Online]. Available: https://www.dspace.espol.edu.ec/bitstream/123456789/56415/1/T-112772 Cando - Medina.pdf; J. D. Murcia Velez and L. F. Chacón Segura, “Diseño de un sistema automático de cultivo hidropónico para forraje verde,” Universidad de La Salle, 2018. [Online]. Available: https://ciencia.lasalle.edu.co/ing_automatizacionF.; P. Radu and L. Gheorghe, “Implementation of an automatic control system of technological process for disinfection of drinking water from treatment plants,” in Proceedings of 2012 IEEE International Conference on Automation, Quality and Testing, Robotics, 2012, pp. 144–149. doi:10.1109/AQTR.2012.6237691.; A. Chiavola, C. Di Marcantonio, M. D’Agostini, S. Leoni, and M. Lazzazzara, “A combined experimental-modeling approach for turbidity removal optimization in a coagulation– flocculation unit of a drinking water treatment plant,” J. Process Control, vol. 130, p. 103068, 2023, doi: https://doi.org/10.1016/j.jprocont.2023.103068.; E. A. Al-Sum, A. Sattar, and M. A. Aziz, “Automation of water treatment plants and its application in power and desalination plants,” Desalination, vol. 92, no. 1–3, 1993, doi:10.1016/0011-9164(93)80087-4.; H. Gulhan et al., “Use of water treatment plant sludge in high-rate activated sludge systems: A techno-economic investigation,” Sci. Total Environ., vol. 901, p. 166431, 2023, doi: https://doi.org/10.1016/j.scitotenv.2023.166431.; A. Ortega Ramírez, L. Cáceres Durán, and L. Castiblanco Molina, “INTRODUCCIÓN AL USO DE COAGULANTES NATURALES EN LOS PROCESOS DE POTABILIZACIÓN DEL AGUA,” Rev. Ambient. Agua, aire y suelo., vol. 11, no. 2, pp. 1–14, 2020, doi: https://doi.org/10.24054/aaas.v11i2.873.; H. A. Díaz Therán, M. Hincapié, L. Montoya, L. Galeano, A. Balaguera, and G. Carvajal, “Evaluación de la sostenibilidad para un sistema individual de potabilización de agua encomunidades rurales a través de la metodología de ACV,” in Encuentro Internacional de Educación en Ingeniería, 2023, 2023, p. 3128. [Online]. Available: 10.26507/paper.3128; R. C. Urban, L. Y. K. Nakada, and R. de L. Isaac, “A system dynamics approach for largescale water treatment plant sludge management: A case study in Brazil,” J. Clean. Prod., vol. 419, p. 138105, 2023, doi: https://doi.org/10.1016/j.jclepro.2023.138105.; N. Unidas, “Objetivo 6: Garantizar la disponibilidad de agua y su gestión sostenible y el saneamiento para todos.,” OBJETIVOS DE DESARROLLO SOSTENIBLE, 2015. https://www.un.org/sustainabledevelopment/es/water-and-sanitation/; C. J. Macuada, A. M. Oddershede, and L. E. Quezada, “DM methodology for automating technology system in water treatment plants,” in 2018 7th International Conference on Computers Communications and Control (ICCCC), 2018, pp. 265–269. doi:10.1109/ICCCC.2018.8390469.; M. Alissa, S. Al-Harahshah, and M. Ibrahim, “Monitoring of Surface Water Quality in King Talal Dam Using GIS: A Case Study,” Iraqi Geol. J., vol. 56, no. 2, pp. 36–47, 2023, doi:10.46717/igj.56.2A.3ms-2023-7-12.; F. Villacís Chimborazo and W. . Zambrano Vélez, “AUTOMATIZACIÓN DEL PROCESO DE TRATAMIENTO DE AGUAS RESIDUALES EN TECNOVA S . A .”,” Universidad Politécnica Salesiana. Ecuador, 2013. [Online]. Available: https://dspace.ups.edu.ec/handle/123456789/4118; M. Portección Social and M. Ambiente Vivienda y Desarrollo Territorial, Resolución 2115 de 2007, vol. 1. 2007, p. 23. [Online]. Available: https://www.minambiente.gov.co/images/GestionIntegraldelRecursoHidrico/pdf/Legislac ión_del_agua/Resolución_2115.pdf.; Ministerio de Desarrollo Económico, “RAS 2000, Titulo A - Aspectos generales de los sistemas de agua potable y saneamiento básico. Ministerio de Vivienda Ciudad y Territorio Colombia,” Reglam. Técnico Del Sect. Agua Potable Y Saneam. Basico, p. 114, 2000.; G. Corporación Alemana, “Manual para la cloración del agua en sistemas de abastecimiento de agua potable en el ambito rural,” Corporación Alem. para la Coop. Int., p. 91, 2017, [Online]. Available: https://sswm.info/sites/default/files/reference_attachments/GIZ 2017. Manual para la cloración del agua en sistemas de abastecimiento de agua potable.pdf; AGUAVIVA, “Sistema de Acueducto,” 2021. https://www.aguavivaesp.gov.co/acueducto/; Anyasi, T. A., Jideani, A. I. O., & Mchau, G. (2013). Functional properties and postharvest utilization of commercial and noncommercial banana cultivars. Comprehensive Reviews in Food Science and Food Safety, 12(5), 509-522. https://doi.org/10.1111/1541-4337.12025; Al-Dairi, M., Pathare, P. B., Al-Yahyai, R., Jayasuriya, H. P. W., & Al-Attabi, Z. (2023). Postharvest Quality, Technologies, and Strategies to Reduce losses along the supply Chain of Banana: a review. Trends in Food Science and Technology, 134, 177-191. https://doi.org/10.1016/j.tifs.2023.03.003; S. A. Vaca Vargas, O. L. García Navarrete, y M. A. Colorado Gómez, “Diseño y construcción de un sistema acuapónico automatizado para cultivo acuaponico NFT de Carpa Roja y Lechuga Crespa”, Visión Electrónica, vol. 17, no. 1, ene. 2023.; Lidyce, Q. L. (s. f.). Elementos teóricos y prácticos sobre la bioimpedancia eléctrica en salud.http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1025- 02552016000500014; Caicedo-Eraso, J.C., Díaz-Arango, F.O., & Osorio-Alturo, A. (2019). Espectroscopia de impedancia eléctrica aplicada al control de la calidad en la industria alimentaria. http://www.scielo.org.co/pdf/ccta/v21n1/0122-8706-ccta-21-01-00100.pdf; Montes, L.M., Mejía-Gutiérrez, L.F., & Caicedo-Eraso, J.C. (2021). Espectroscopia de impedancia eléctrica, una herramienta para aplicaciones biotecnológicas con Lactobacillus casei ATCC 393. http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0123- 34752021000100055; Ocampo Hernández, Ó.H., Ruiz Villa, C.A., Aristizábal Botero, W., Olarte Echeverri, G., Gallego, P.A. (2017). Caracterización del tejido columnar del cérvix mediante espectroscopia de impedancia eléctrica y modelado computacional. Biosalud. https://www.semanticscholar.org/paper/216f9823cf95e0f9043636a052f656c4d318eed1; García Bello, J., Batista Luna, T., & Rodríguez de la Cruz, N. (2023). Principios básicos y uso en medicina de la espectroscopia de impedancia. Revista Cubana de Medicina Militar, 52(2), e02302316. Recuperado de https://revmedmilitar.sld.cu/index.php/mil/article/view/2316/1772; Carreño, A., & Gómez, C. (2013). Procesamiento de tejido de cuello uterino para estudio piloto de detección temprana de cáncer cervical basado en espectroscopia de impedancia eléctrica.; N. A. Ramírez-Pérez, L. E. Aparicio-Pico, y C. A. Pérez-Triana, “Medición sobre MRI para diagnóstico de cáncer de próstata”, Visión Electrónica, vol. 14, no. 2, pp. 196–206, jul. 2020. https://doi.org/10.14483/22484728.17965; Li, Yunhua; Cai, Chaozhi; Lee, Kok-Meng; Teng, Fengjian “A novel cascade temperature control system for a high-speed heat-airflow wind tunnel”, IEEE/ASME Transactions on Mechatronics, volumen 18, Issue 4, pages 1310 - 1319, 2013. https://doi:10.1109/TMECH.2013.2262077; Cai, Chaozhi; Li, Yunhua; Dong, Sujun, “Experimental Study on Gas Temperature Control for a High-Speed Heat-Airflow Wind Tunnel”, Journal of Aerospace Engineering, vol. 29, Issue. 6, nov 2016. https://doi.org/10.14483/22487638.6071; J. H. Fresneda-Alarcón, A. Escobar-Diaz, H. Vacca-González, y G. J. Rincón-Aponte, “Modelamiento e implementación de una planta térmica”, Visión Electrónica, vol. 15, no. 1, pp. 94–103, feb. 2021. https://doi.org/10.14483/22484728.17470; J. G. Ascanio-Villabona, B. E. Tarazona-Romero, y C. L. Sandoval, “Study of the behavior of the photovoltaic panel according to the installed surface”, Visión Electrónica, vol. 16, no. 2, dic. 2022.; LIU, Wei; ZHOU, Mengde, “An active damping vibration control system for wind tunnel models”, Chinese Journal of Aeronautics, vol. 32, pp. 2109-2120, sept 2019. https://doi.org/10.1016/j.cja.2019.04.014; Huang, Rui; Zhao, Yonghui; Hu, Haiyan, “Wind-Tunnel tests for active flutter control and closed-loop flutter identification”, AIAA Journal, vol. 54, Issue 7, pp. 2089-2099, 2016. https://doi.org/10.2514/1.J054649; FEEDBACK PT 326 Process Trainer User manual (e-lab) Crowborough, E. Sussex, England, 1999.; FEEDBACK Industry - PT 326 Process Trainer owner guide Crowborough, E. Sussex, England, 1999.; C. B. S. Dutra, F. K. Mendonca, G. C. Sousa, and N. G. Bonacorso, "Retrofitting of a plain table plotter for printed circuit boards prototyping," in Power Electronics Conference, 2009. COBEP '09. Brazilian, 2009, pp. 1027-1032.; K. Salonitis and S. Vatousianos, "Experimental Investigation of the Plasma Arc Cutting Process," Procedia CIRP, vol. 3, pp. 287-292, // 2012.; Lida Pan; Xiangkun Guo; Yan Luan; Hongliang Wang, “Design and realization of cutting simulation function of digital twin system of CNC machine tool”, Procedia Computer Science, vol. 183, pp. 261-266, 2021. https://doi.org/ https://doi.org/10.1016/j.procs.2021.02.057; A.M. Madni, C.C. Madni, S.D. Lucero, “Leveraging digital twin technology in modelbased systems engineering”, Systems, vol. 7, 2019. https://doi.org/ https://doi.org/10.3390/systems7010007; Ran, Meng, “Research on the key Technology of contour error control of machine tool based on digital twin”, ACM International Conference Proceeding Series, pp. 1070- 1075, dec 2022. https://doi.org/10.1145/3584376.3584567; Yu. G. KabaldinL, “Digital Twin for 3D Printing on CNC Machines”, Russian Engineering Research, vol. 39, pp. 848-851, 2019. https:// doiorg.bdigital.udistrital.edu.co/10.3103/S1068798X19100101; Hershberger, R. E., Morales, A. & Siegfried, J. D. Clinical and genetic issues in dilated cardiomyopathy: a review for genetics professionals. Genet. Med. 12, 655–667 (2010). This review article provides a wide and detailed overview of clinical and genetic issues in specific types of genetic DCM.; Hershberger, R.E.; Hedges, D.J.; Morales, A. Dilated cardiomyopathy: The complexity of a diverse genetic architecture. Nat. Rev. Cardiol. 2013, 10, 531–547.; Antunes M de O, Scudeler TL. Hypertrophic cardiomyopathy. IJC Hear Vasc. 2020;27:100503.; Teekakirikul P, Zhu W, Huang HC, Fung E. Hypertrophic cardiomyopathy: An overview of genetics and management. Biomolecules. 2019;9(12):1–11.; Maron BJ. Clinical Course and Management of Hypertrophic Cardiomyopathy. N Engl J Med. 2018;379(7):655–68.; Maron, B. J. Contemporary definitions and classification of the cardiomyopathies: an American Heart Association scientific statement from the Council on Clinical Cardiology, Heart Failure and Transplantation Committee; Quality of Care and Outcomes Research and Functional Genomics and Translational Biology Interdisciplinary Working Groups; and Council on Epidemiology and Prevention. Circulation 113, 1807–1816 (2006).; Elliott, P. et al. Classification of the cardiomyopathies: a position statement from the european society of cardiology working group on myocardial and pericardial diseases. Eur. Heart J. 29, 270–276 (2007).; Richardson, P. et al. Report of the 1995 World Health Organization/International Society and Federation of Cardiology Task Force on the definition and classification of cardiomyopathies. Circulation 93, 841–842 (1996); Rostán, S., Smiliansky, N., & Vaucher, A. (2020). Miocardiopatía por Influenza A H1N1. Reporte de un caso clínico. Revista Uruguaya De Medicina Interna, 5(3), 26-30. https://doi.org/10.26445/05.03.4; Galarza, G., Moreno, J., & Vasquez, G., (2021). Miocardiopatia secundaria a influenza. Revista Médica Vozandes, 32(1), 84-87. DOI:10.48018/rmv.v32.i1.2; Z. Wang, H. Shen, Y. Liu, Y. Cheng, R. Zhang, X. Wang, and A. L. Yuille, “Improving the accuracy of medical diagnosis with causal machine learning,” Nature Communications, vol. 11, no. 1, p. 18310, 2020.; M. M. Ahsan and Z. Siddique, “Machine learning-based heart disease diagnosis: A systematic literature review,” Artificial Intelligence in Medicine, vol. 128, p. 102289, 2022. [Online]. Available: https: //www.sciencedirect.com/science/article/pii/S0933365722000549; A. Kumar and A. Singla, “Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda,” Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 7, pp. 1–28, 2022.; U. S. Acharya, S. Kulkarni, and P. Raju, “Artificial intelligence appliedto cardiomyopathies: Is it time for clinical application?” IEEE Access, vol. 10, pp. 16 264–16 282, 2022.; A. Regueiro Gómez, C. B. Busoch Morlán, C. Regueiro Busoch, y R. J. Díaz Martínez, “Biomedical Engineering: experiences in the research formation with MOODLE”, Visión Electrónica, vol. 14, no. 2, pp. 152–158, jul. 2020.; B. Forero, K. Velásquez, R. Hernández, y E. Mejía, “Simulation of transradial prosthesis using Virtual Reality Environment and electrooculography (EOG) signals for grip therapy”, Vis. Electrónica, vol. 16, no. 2, ago. 2022.; D. Sánchez-L., G. Sánchez, y L. A. Luengas-C., “Static postural stability: analysis in time and frequency through the development of a software tool”, Visión Electrónica, vol. 17, no. 1, abr. 2023.; J. L. Gerardo‐Nava, et al. "Transformative Materials to Create 3D Functional Human Tissue Models In Vitro in a Reproducible Manner." Advanced Healthcare Materials (2023): 2301030. doi.org/10.1002/adhm.202301030; C. Vesga-Castro, et al. “Contractile force assessment methods for in vitro skeletal muscle tissues.” eLife vol. 11 e77204. doi:10.7554/eLife.77204; K. Budde, J. Zimmermann, E. Neuhaus, M. Schröder, A. M. Uhrmacher and U. van Rienen, "Requirements for Documenting Electrical Cell Stimulation Experiments for Replicability and Numerical Modeling," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 1082-1088, doi:10.1109/EMBC.2019.8856863.; A.M. Kasper, et al. “Mimicking exercise in three-dimensional bioengineered skeletal muscle to investigate cellular and molecular mechanisms of physiological adaptation.” Journal of cellular physiology vol. 233,3 (2018): 1985-1998. doi:10.1002/jcp.25840; M. Flaibani, et al. “Muscle differentiation and myotubes alignment is influenced by micropatterned surfaces and exogenous electrical stimulation.” Tissue engineering. Part A vol. 15,9 (2009): 2447-57. doi:10.1089/ten.tea.2008.0301; Fernández‐Costa, Juan M., et al. "Training‐on‐a‐Chip: A Multi‐Organ Device to Study the Effect of Muscle Exercise on Insulin Secretion in Vitro." Advanced Materials Technologies. vol. 8, no 7, p. 2200873 (2023). doi.org/10.1002/admt.202200873; Zhang, Xiaoning, et al. "Complex refractive indices measurements of polymers in visible and near-infrared bands." Applied optics. vol. 59, no 8, p. 2337-2344 (2020). Doi:org/10.1364/AO.383831; J. Fukushima, et al. “Effect of Aspect Ratio on the Permittivity of Graphite Fiber in Microwave Heating.” Materials (Basel, Switzerland) vol. 11,1 169. 22 Jan. 2018, doi:10.3390/ma11010169; K. K. Ravikumar, and K.K. Palanivelu. "Dielectric properties of natural rubber composites filled with graphite." Materials Today: Proceedings 16 (2019): 1338-1343. doi.org/10.1016/j.matpr.2019.05.233; S. Chen. “Dielectric constant measurement of P3HT, polystyrene, and polyethylene”, PhD. thesis., Faculty of Science and Engineering, 2017.; X. Y. Qi, et al. “Enhanced electrical conductivity in polystyrene nanocomposites at ultralow graphene content.” ACS applied materials & interfaces vol. 3,8 (2011): 3130-3. doi:10.1021/am200628c:10; K. Gadonna, et al. "Study of gas heating by a microwave plasma torch." Journal of Modern Physics. vol. 3, no 10, p. 1603. (2012): Doi.org/10.4236/jmp.2012.330198; E. Seran, et al. "What we can learn from measurements of air electric conductivity in 222Rn‐rich atmosphere." Earth and Space Science. vol. 4, no 2, p. 91-106 (2017). doi.org/10.1002/2016EA000241; K. Izdihar, et al. "Structural, mechanical, and dielectric properties of polydimethylsiloxane and silicone elastomer for the fabrication of clinical-grade kidney phantom." Applied Sciences. vol. 11, no 3, p. 1172 (2021). DOI:10.3390/app11031172; A. Müller, M. C. Wapler, and U. Wallrabe. "A quick and accurate method to determine the Poisson's ratio and the coefficient of thermal expansion of PDMS." Soft Matter. vol. 15, no 4, p. 779-784 (2019). DOI:10.1039/C8SM02105H; AZoM.com. (n.d.). Properties: Carbon - Graphite Materials. 2012.; Polystyrene %7C Designerdata. (n.d.). https://designerdata.nl/materials/plastics/thermoplastics/polystyrene; Poisson’s Ratio. (n.d.). https://polymerdatabase.com/polymer%20physics/Poisson%20Table.html; S, Shauheen, et al. “The elastic modulus of Matrigel as determined by atomic force microscopy.” Journal of structural biology. vol. 167, no 3, p. 216-219. doi:10.1016/j.jsb.2009.05.005; J.J. Vaca-González, et al. "Effect of electrical stimulation on chondrogenic differentiation of mesenchymal stem cells cultured in hyaluronic acid–Gelatin injectable hydrogels." Bioelectrochemistry. vol. 134, p. 107536 (2020). doi:10.1016/j.bioelechem.2020.107536; G. Agrawal, et al. “Skeletal muscle-on-a-chip: an in vitro model to evaluate tissue formation and injury.” Lab on a chip vol. 17,20 (2017): 3447-3461. doi:10.1039/c7lc00512a; G.; Renganathan et al., “ETH Library Foot Biomechanics with Emphasis on the Plantar Pressure Sensing: A Review Foot Biomechanics with Emphasis on the Plantar Pressure Sensing: A Review,” in Revolutions in Product Design for Healthcare, D. S. and Innovation, Ed. Singapore: Springer, 2022.; A. K. Buldt, J. J. Allan, K. B. Landorf, and H. B. Menz, “The relationship between foot posture and plantar pressure during walking in adults: A systematic review,” Gait and Posture, vol. 62. 2018, doi:10.1016/j.gaitpost.2018.02.026.; C. Deng, W. Tang, L. Liu, B. Chen, M. Li, and Z. L. Wang, “Self -Powered Insole Plantar Pressure Mapping System,” Adv. Funct. Mater., vol. 28, no. 29, Jul. 2018, doi:10.1002/ADFM.201801606.; J. L. Chen et al., “Plantar Pressure-Based Insole Gait Monitoring Techniques for Diseases Monitoring and Analysis: A Review,” Adv. Mater. Technol., vol. 7, no. 1, p. 2100566, Jan. 2022, doi:10.1002/ADMT.202100566.; Q. Zhang, Y. L. Wang, Y. Xia, X. Wu, T. V. Kirk, and X. D. Chen, “A low-cost and highly integrated sensing insole for plantar pressure measurement,” Sens. Bio-Sensing Res., vol. 26, 2019, doi:10.1016/j.sbsr.2019.100298.; J. F. Hafer, M. W. Lenhoff, J. Song, J. M. Jordan, M. T. Hannan, and H. J. Hillstrom, “Reliability of plantar pressure platforms,” Gait Posture, vol. 38, no. 3, 2013, doi:10.1016/j.gaitpost.2013.01.028.; H. Deepashini, B. Omar, A. Paungmali, N. Amaramalar, H. Ohnmar, and J. Leonard, “An insight into the plantar pressure distribution of the foot in clinical practice: Narrative review,” Polish Annals of Medicine, vol. 21, no. 1. 2014, doi:10.1016/j.poamed.2014.03.003.; K. Hébert-Losier and L. Murray, “Reliability of centre of pressure, plantar pressure, and plantar-flexion isometric strength measures: A systematic review,” Gait and Posture, vol. 75. 2020, doi:10.1016/j.gaitpost.2019.09.027.; P. R. Cavanagh, F. G. Hewitt, and J. E. Perry, “In-shoe plantar pressure measurement: a review,” The Foot, vol. 2, no. 4. 1992, doi:10.1016/0958-2592(92)90047-S.; X. Li, K. Wang, Y. L. Wang, and K. C. Wang, “Plantar pressure measurement system based on piezoelectric sensor: a review,” Sensor Review, vol. 42, no. 2. 2022, doi:10.1108/SR-09-2021-0333.; A. Ciniglio, A. Guiotto, F. Spolaor, and Z. Sawacha, “The design and simulation of a 16- sensors plantar pressure insole layout for different applications: From sports to clinics, a pilot study,” Sensors, vol. 21, no. 4, 2021, doi:10.3390/s21041450.; L. Luengas- Contreras.,and L. Wanumen-Silva. "Modelos computacionales en la posturografía". Tecnura, vol. 26, no. 73, 2022, 30-48. https://doi.org/10.14483/22487638.18060; R. de Fazio, E. Perrone, R. Velázquez, M. De Vittorio, and P. Visconti, “Development of a self-powered piezo-resistive smart insole equipped with low-power ble connectivity for remote gait monitoring,” Sensors, vol. 21, no. 13, 2021, doi:10.3390/s21134539.; H. Muhedinovic and D. Boskovic, “Design of iot solution for velostat footprint pressure sensor system,” in Lecture Notes of the Institute for Computer Sciences, SocialInformatics and Telecommunications Engineering, LNICST, 2016, vol. 187, doi:10.1007/978-3-319-51234-1_30.; AICMA, «Estadísticas de víctimas». Accedido: 26 de octubre de 2023. [En línea]. Disponible en: https://www.accioncontraminas.gov.co/Estadisticas/Paginas/Estadisticasde-Victimas.aspx; G. R. Hurley, R. McKenney, M. Robinson, M. Zadravec, y M. R. Pierrynowski, «The role of the contralateral limb in below-knee amputee gait», Prosthet Orthot Int, vol. 14, n.o 1, Art. n.o 1, abr. 1990, doi:10.3109/03093649009080314.; M. S. Pinzur, «The Effect of Prosthetic Alignment on Relative Limb Loading in Persons with Transtibial Amputation: A Preliminary Report», p. 5, 1995.; R. Gailey, «Review of secondary physical conditions associated with lower-limb amputation and long-term prosthesis use», The Journal of Rehabilitation Research and Development, vol. 45, n.o 1, Art. n.o 1, dic. 2008, doi:10.1682/JRRD.2006.11.0147.; T. Kobayashi, M. S. Orendurff, y D. A. Boone, «Dynamic alignment of transtibial prostheses through visualization of socket reaction moments», Prosthetics and orthotics international, vol. 39, n.o 6, Art. n.o 6, 2015.; D. A. Boone et al., «Perception of socket alignment perturbations in amputees with transtibial prostheses», The Journal of Rehabilitation Research and Development, vol. 49, n.o 6, Art. n.o 6, 2012, doi:10.1682/JRRD.2011.08.0143.; H. Hashimoto, T. Kobayashi, F. Gao, y M. Kataoka, «A proper sequence of dynamic alignment in transtibial prosthesis: insight through socket reaction moments», Sci Rep, vol. 13, n.o 1, Art. n.o 1, ene. 2023, doi:10.1038/s41598-023-27438-1; S. L. Delp et al., «OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement», IEEE Transactions on Biomedical Engineering, vol. 54, n.o 11, Art. n.o 11, nov. 2007, doi:10.1109/TBME.2007.901024.; F. De Groote, A. L. Kinney, A. V. Rao, y B. J. Fregly, «Evaluation of Direct Collocation Optimal Control Problem Formulations for Solving the Muscle Redundancy Problem», Ann Biomed Eng, vol. 44, n.o 10, Art. n.o 10, oct. 2016, doi:10.1007/s10439-016-1591-9.; G. Serrancoli et al., «Subject-Exoskeleton Contact Model Calibration Leads to Accurate Interaction Force Predictions», IEEE Trans. Neural Syst. Rehabil. Eng., vol. 27, n.o 8, pp. 1597-1605, ago. 2019, doi:10.1109/TNSRE.2019.2924536.; S. Miller y Y. V. Weddingen, «Modeling Flexible Bodies with Simscape Multibody Software», 2017. Accedido: 10 de agosto de 2023. [En línea]. Disponible en: https://la.mathworks.com/content/dam/mathworks/tag-team/Objects/s/Modeling-FlexibleBodies-Simscape-Multibody-171122.pdf; M. Ackermann y A. J. van den Bogert, «Optimality Principles for Model-Based Prediction of Human Gait», J Biomech, vol. 43, n.o 6, Art. n.o 6, abr. 2010, doi:10.1016/j.jbiomech.2009.12.012.; T. W. Dorn, J. M. Wang, J. L. Hicks, y S. L. Delp, «Predictive Simulation Generates Human Adaptations during Loaded and Inclined Walking», PLOS ONE, vol. 10, n.o 4, Art. n.o 4, abr. 2015, doi:10.1371/journal.pone.0121407.; C. L. Dembia, N. A. Bianco, A. Falisse, J. L. Hicks, y S. L. Delp, «OpenSim Moco: Musculoskeletal optimal control», PLOS Computational Biology, vol. 16, n.o 12, p. e1008493, dic. 2020, doi:10.1371/journal.pcbi.1008493.; L. Nolan, A. Wit, K. Dudziñski, A. Lees, M. Lake, y M. Wychowañski, «Adjustments in gait symmetry with walking speed in trans-femoral and trans-tibial amputees», Gait Posture, vol. 17, n.o 2, pp. 142-151, abr. 2003, doi:10.1016/s0966-6362(02)00066-8.; L. Nolan y A. Lees, «The functional demands on the intact limb during walking for active transfemoral and transtibial amputees», Prosthetics & Orthotics International, vol. 24, n.o 2, pp. 117-125, ago. 2000, doi:10.1080/03093640008726534.; W. Herzog, B. M. Nigg, L. J. Read, y E. Olsson, «Asymmetries in ground reaction force patterns in normal human gait», Medicine & Science in Sports & Exercise, vol. 21, n.o 1, p. 110, feb. 1989.; M. Roerdink, S. Roeles, S. C. H. van der Pas, O. Bosboom, y P. J. Beek, «Evaluating asymmetry in prosthetic gait with step-length asymmetry alone is flawed», Gait & Posture, vol. 35, n.o 3, pp. 446-451, mar. 2012, doi:10.1016/j.gaitpost.2011.11.005.; M. Roerdink y P. J. Beek, «Understanding Inconsistent Step-Length Asymmetries Across Hemiplegic Stroke Patients: Impairments and Compensatory Gait», Neurorehabil Neural Repair, vol. 25, n.o 3, pp. 253-258, mar. 2011, doi:10.1177/1545968310380687.; GP Fishwick, “Una introducción a Opensimulator y aplicaciones M&S basadas en agentes de entornos virtuales”, en Simulation Conference (WSC), Actas del invierno de 2009, diciembre de 2009, págs. 177 a 183,64.; Linden Research, Inc. Disponible en: http://lindenlab.com; M. Barbulescu, M. Marinescu, O. Grigoriu, G. Neculoiu, V. Sandulescu e I. Halcu, "GNU,GPL en el estudio de programas del campo de la ingeniería de sistemas", en Roedunet International Conference (RoEduNet), 10 de junio de 2011, pp. 1 –4.; Visor Hippo OpenSim, disponible: http://mjmlabs.com/viewer; Visor RealXtend, disponible: http://realxtend.org; M. Pattal, Y. Li y J. Zeng, “Web 3.0: ¡una verdadera web personal! Más oportunidades y más amenazas”, en Aplicaciones, servicios y tecnologías móviles de próxima generación, 2009. NGMAST '09. Tercera Internacional, Conferencia sobre, septiembre de 2009, pp. 125 –128.; McLeod, S. A; Piaget “Cognitive Theory” (en inglés). Simply Psychology. Consultado el 18 de marzo 2023.; Bronkart, J. P. y otros (1985). Vigotsky aujourd’hui. París: Delachaux & Niestlé. Consultado el 18 de marzo 2023; Bruner, J. (1980). Investigación sobre el desarrollo cognitivo. España: Pablo del Río.; Papert, S., & Harel, I. (2002). Situar el construccionismo. Alajuela: INCAE.; Ausubel, D. P. (2002). Adquisición y retención del conocimiento. Una perspectiva cognitiva. Barcelona: Ed. Paidós.; Athanassopoulos, N. Capítulo 7: Estudio comparativo del desarrollo de las inteligencias múltiples en alumnos que cursan o no estudios de danza en un conservatorio. innovando en educación.; Lave, J. (1991). Situating learning in communities of practice. En H. Resnick, S. Levine, & S. Teasley (Eds.), Perspective on socially shared cognition (pp.63-82). Washington, Estados Unidos: American Psycological Association.; Von Glasersfeld, E. 1984. An introduction to radical constructivism. En: P. Watzlawick. Theinvented reality. New York: Norton, pp. 17-40; MIT Media Lab (2016). Professor Emeritus Seymour Papert, pioneer of constructionist learning, dies at 88. MIT News, en http://news.mit.edu/2016/seymourpapertpioneer-of- constructionist-learning-dies-0801; Desarrollo de una aplicación con PLC Siemens, https://educatia.com.co/programacion-plc-logo-siemens-grafcet-a-ladder/; W. A. Bhat, A. Alzahrani, and M. A. Wani, “Can computer forensic tools be trusted in digital investigations?” Science and Justice, vol. 61, no. 2, pp. 198–203, Mar. 2021, [Online]. Disponible en: 10.1016/j.scijus.2020.10.002.; B. K. Akcam, “Forensic Science International we should give special mention to the observance of secrecy in the automotive industry in case of security relevant systems Digitizing Forensic Laboratories: The Turkish Criminal Police Laboratories Case.”; L. Xu, B. Wang, L. Wang, D. Zhao, X. Han, and S. Yang, “PLC-SEIFF: A programmable logic controller security incident forensics framework based on automatic construction of security constraints,” Computers and Security, vol. 92, May 2020, [Online]. Disponible en: 10.1016/j.cose.2020.101749.; M. I. Cohen, D. Bilby, and G. Caronni, “Distributed forensics and incident response in the enterprise,” in Digital Investigation, 2011, vol. 8, no. SUPPL. [Online]. Disponible en: 10.1016/j.diin.2011.05.012.; C. J. Courtney Mustaphi et al., “Guidelines for reporting and archiving 210Pb sediment chronologies to improve fidelity and extend data lifecycle,” Quaternary Geochronology, vol. 52, pp. 77–87, Jun. 2019, [Online]. Disponible en: 10.1016/j.quageo.2019.04.003.; P. Lutta, M. Sedky, M. Hassan, U. Jayawickrama, and B. Bakhtiari Bastaki, “The complexity of internet of things forensics: A state-of-the-art review,” Forensic Science International: Digital Investigation, vol. 38. Elsevier Ltd, Sep. 01, 2021. [Online]. Disponible en: 10.1016/j.fsidi.2021.301210.; W. Halboob, R. Mahmod, N. I. Udzir, and M. D. T. Abdullah, “Privacy levels for computer forensics: Toward a more efficient privacy-preserving investigation,” in Procedia Computer Science, 2015, vol. 56, no. 1, pp. 370–375. doi:10.1016/j.procs.2015.07.222.; G. Ma, Z. Wang, L. Zou, and Q. Zhang, “Computer forensics model based on evidence ring and evidence chain,” in Procedia Engineering, 2011, vol. 15, pp. 3663–3667.; M. Saadoon, S. H. Siti, H. Sofian, H. H. M. Altarturi, Z. H. Azizul, and N. Nasuha, “Fault tolerance in big data storage and processing systems: A review on challenges and solutions,” Ain Shams Engineering Journal, vol. 13, no. 2. Ain Shams University, Mar. 01, 2022.; D. Closser and E. Bou-Harb, “A live digital forensics approach for quantum mechanical computers,” Forensic Science International: Digital Investigation, vol. 40, p. 301341, Apr. 2022; G. Koorey, S. McMillan, and A. Nicholson, “Incident Management and Network Performance,” in Transportation Research Procedia, 2015, vol. 6, pp. 3–16.; K. Barik, S. Das, K. Konar, B. Chakrabarti Banik, and A. Banerjee, “Exploring user requirements of network forensic tools,” Global Transitions Proceedings, vol. 2, no. 2, pp. 350–354, Nov. 2021.; A. M. Marshall, “Digital forensic tool verification: An evaluation of options for establishing trustworthiness,” Forensic Science International: Digital Investigation, vol. 38, Sep. 2021.; T. Wu, F. Breitinger, and S. O’Shaughnessy, “Digital forensic tools: Recent advances and enhancing the status quo,” Forensic Science International: Digital Investigation, vol. 34, Sep. 2020.; W. A. Bhat, A. AlZahrani, and M. A. Wani, “Can computer forensic tools be trusted in digital investigations?” Science and Justice, vol. 61, no. 2, pp. 198–203, Mar. 2021.; A. Daniel D and S. E. Roslin, “Data validation and integrity verification for trust-based data aggregation protocol in WSN,” Microprocessors and Microsystems, vol. 80. Elsevier B.V., Feb. 01, 2021.; J. Tian and X. Jing, “Cloud data integrity verification scheme for associated tags,” Computers and Security, vol. 95, Aug. 2020.; C. Yang, F. Zhao, X. Tao, and Y. Wang, “Publicly verifiable outsourced data migration scheme supporting efficient integrity checking,” Journal of Network and Computer Applications, vol. 192, Oct. 2021.; Q. Zhao, S. Chen, Z. Liu, T. Baker, and Y. Zhang, “Blockchain-based privacypreserving remote data integrity checking scheme for IoT information systems,” Information Processing and Management, vol. 57, no. 6, Nov. 2020.; K. Porter, R. Nordvik, F. Toolan, and S. Axelsson, “Timestamp prefix carving for filesystem metadata extraction,” Forensic Science International: Digital Investigation, vol. 38, Sep. 2021.; R. Nordvik, K. Porter, F. Toolan, S. Axelsson, and K. Franke, “Generic Metadata Time Carving,” Forensic Science International: Digital Investigation, vol. 33, Jul. 2020.; M. Kiweler, M. Looso, and J. Graumann, “MARMoSET – Extracting Publication-ready Mass Spectrometry Metadata from RAW Files,” Molecular and Cellular Proteomics, vol. 18, no. 8, pp. 1700–1702, 2019.; N. K. Booker, P. Knights, J. D. Gates, and R. E. Clegg, “Applying principal component analysis (PCA) to the selection of forensic analysis methodologies,” Engineering Failure Analysis, vol. 132, Feb. 2022.; J. W. Ma, T. Czerniawski, and F. Leite, “An application of metadata-based image retrieval system for facility management,” Advanced Engineering Informatics, vol. 50, Oct. 2021.; L.E. Aparicio, “Informe Diagnóstico del estado actual de uso de las historias clínicas en hospitales de Bogotá”, 2010.; B. Schneier. Beyind Fear: Thinking Sensibly about Security in an Uncertain World. Copernicus Books, New York, NY, 2003.; R. Campbell, J. Al-Muhtadi, P. Naldurg, G. Sampemane, and M. Mickunas. Towards Security of Privacy for Pervasive Computing. En Proceedings of the International Symposium on Software Security, LNCS 2603, páginas 1-15, Springer-Verlag, 2002.; D. Garlan, D. Siewiprek, A. Smailagic, and P. Steenkiste. Project AURA: Toward Distraction-Free Pervasive Computing. IEEE Pervasive computing, 1(2):22-31, 2002.; M. Ulrich Legacy Systems: Transformation Strategies. Prentice Hall PTR, 2002.; J. H. Saltzer, D. P. Reed, and D.D. Clark. End-to-End Arguments in System Desing. ACM transactions on Computer Systems, 2(4):277-288, 1984.; Presentación del libro “Seguridad: una Introducción” Dr. MANUTA, Giovanni. Consultor y profesor de seguridad Cranfield University. Revista de Seguridad Corporativa. http//: www.seguridadcorporativa.org.; BORGHELLO. Cristian F. Tesis Seguridad Informática: Sus implicaciones e implementación. [En línea]. Junio 2001, (Citado nov., 05, 2004). Disponible en Internet:; FISHER ROYAL P. “Seguridad en los temas informáticos, Madrid; p 85, 1998.; JIMENEZ, José Alfredo. Evolución Seguridad de un Sistema de Información. [en línea]. Noviembre 2001, (Citado mar., 16, 2005). Disponible en Internet:; CALVO, Rafael Fernández. Glosario básico inglés-español para usuarios. [En línea]. Febrero 2000, (Citado mar., 16, 2005). Disponible en Internet:; ARDITA, Julio Cesar. Director de Cybsec S.A. Security System y ex-Hacker. Entrevista personal realizada el día 15 de enero del 2001 en Instalaciones de Cybsec S.A. http//: www.cybsec.com; MERLAT, Máximo. PAZ, Gonzalo. SOSA, Matias. MARTINEZ, Marcelo. Seguridad Informática: Hackers. [En línea]. Julio 2003. (Citado mar., 16, 2005). Disponible en Internet: http.//www.Seguridad InformáticaHackerilustrados_com.htm; KEITHE J. Jones, Superutilidades Hackers. México D.F: Mac Graw Hill, 2003, p. 282-288.; SUÑER, Francisco José. Hacker. [En línea]. Julio 2004. (Citado abr., 15, 2005). Disponible en Internet:< http://www.ciencia-ficcion.com/glosario/hacker.htm>; CANO. Jeimy. V Encuesta Nacional sobre Seguridad Informática en Colombia. [En línea]. Enero 2005, (Citado jul., 25, 2005). Disponible en Internet:; MENDEZ. Carlos E. Metodología Diseño y Desarrollo del Proceso de Investigación. Bogotá: Mc Graw Hill, 2005.; M. Bano, A. Qayyum, R. N. Bin Rais, and S. S. A. Gilani, “Soft-Mesh: A Robust Routing Architecture for Hybrid SDN and Wireless Mesh Networks,” IEEE Access, vol. 9, pp. 87715–87730, 2021, doi:10.1109/ACCESS.2021.3089020.; S. Kemp, “Digital in 2018: World’s internet users pass the 4 billion mark - We Are Social UK,” 2018. https://wearesocial.com/uk/blog/2018/01/global-digital-report-2018/ (accessed Sep. 01, 2023).; Z. Latif, K. Sharif, F. Li, M. Karim, and Y. Wang, “A Comprehensive Survey of Interface Protocols for Software Defined Networks,” 2019.; M. Paliwal and K. K. Nagwanshi, “Effective Flow Table Space Management Using PolicyBased Routing Approach in Hybrid SDN Network,” IEEE Access, vol. 10, pp. 59806– 59820, 2022, doi:10.1109/ACCESS.2022.3180333.; “Management, Control and Data plane - Cisco Community.” https://community.cisco.com/t5/switching/management-control-and-data-plane/tdp/2803553 (accessed Sep. 02, 2023).; “Management, Control, and Data Planes in Network Devices and Systems « ipSpace.net blog,” 2013. https://blog.ipspace.net/2013/08/management-control-and-data-planesin.html (accessed Mar. 12, 2023).; H. Farag, “CCNA-SEC Lec#4 %7C Securing Data Plane – Network-Masters,” 2017. https://networkmasters.wordpress.com/2017/01/27/ccna-sec-lec4-securing-data-plane/ (accessed Mar. 12, 2023).; “Difference Between Data Plane Vs Control Plane - Route XP Private Network Services.” https://www.routexp.com/2020/03/difference-between-data-plane-vs.html (accessed Mar. 12, 2023).; “Cisco SDN: Control Plane e Data Plane - Cisco Community.” https://community.cisco.com/t5/blogs-routing-y-switching/cisco-sdn-control-plane-edata-plane/ba-p/4655704 (accessed Sep. 02, 2023).; M. Jammal, T. Singh, A. Shami, R. Asal, and Y. Li, “Software defined networking: State of the art and research challenges,” 2014, doi:10.1016/j.comnet.2014.07.004.; C. Chaudet and Y. Haddad, “Wireless software defined networks: Challenges and opportunities,” 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronic Systems, COMCAS 2013, 2013, doi:10.1109/COMCAS.2013.6685237.; J. F. G. Orrego and J. P. U. Duque, “Throughput and delay evaluation framework integrating SDN and IEEE 802.11s WMN,” 2017 IEEE 9th Latin-American Conference on Communications, LATINCOM 2017, vol. 2017-January, pp. 1–6, Dec. 2017, doi:10.1109/LATINCOM.2017.8240186.; A. Drescher, “A Survey of Software-Defined Wireless Networks”, Accessed: Sep. 02, 2023. [Online]. Available: http://www.cse.wustl.edu/~jain/cse574-14/ftp/sdwn/index.html; D. Kreutz, F. M. V. Ramos, P. E. Verissimo, C. E. Rothenberg, S. Azodolmolky, and S. Uhlig, “Software-defined networking: A comprehensive survey,” Proceedings of the IEEE, vol. 103, no. 1, pp. 14–76, Jan. 2015, doi:10.1109/JPROC.2014.2371999.; F. D. O. Silva, J. H. D. S. Pereira, P. F. Rosa, and S. T. Kofuji, “Enabling future internet architecture research and experimentation by using software defined networking,” Proceedings - European Workshop on Software Defined Networks, EWSDN 2012, pp. 73–78, 2012, doi:10.1109/EWSDN.2012.24.; E. Haleplidis and S. Salsano, “Overview of RFC7426: SDN Layers and Architecture Terminology - IEEE Software Defined Networks,” 2017. https://sdn.ieee.org/newsletter/september-2017/overview-of-rfc7426-sdn-layers-andarchitecture-terminology (accessed Feb. 18, 2023).; J. Espinoza, “Las API en Ambientes de Controladores de Red — Serie SDN №2 %7C by Jesus Espinoza %7C Medium,” 2021. https://jesuseduardoespinoza.medium.com/las-api-enambientes-de-controladores-de-red-serie-sdn-2-75139f6a10a2 (accessed Mar. 13, 2023).; J. E. Cáceres Guevara and C. A. Casilimas Fajardo, “Arquitectura y funcionamiento de redes definidas por software (SDN),” Repositorio Universidad Distrital Francisco José de Caldas, 2022.; “Open Networking Foundation.” https://opennetworking.org/ (accessed Sep. 07, 2023).; “Overview of Northbound Interfaces - eSight 21.0 Operation Guide 07 - Huawei.” https://support.huawei.com/enterprise/es/doc/EDOC1100208263/8ac892ef/northboundinterfaces (accessed Mar. 13, 2023).; D. J. Ramos Suavita, “Análisis de vulnerabilidades a nivel de seguridad en redes SDN para los planos de control y plano de datos,” Universidad Militar Nueva Granada, 2021, Accessed: Nov. 05, 2022. [Online]. Available: https://repository.unimilitar.edu.co/bitstream/handle/10654/41314/RamosSuavitaDairon Javier2022.pdf?sequence=1&isAllowed=y; L. Zhu, M. M. Karim, K. Sharif, F. Li, X. Du, and M. Guizani, “SDN Controllers: Benchmarking & Performance Evaluation,” Feb. 2019, [Online]. Available: http://arxiv.org/abs/1902.04491; D. Dudhal, “Performance Evaluation of SDN Controllers using Cbench and Iperf %7C by Disha Dudhal %7C Medium,” 2022. https://medium.com/@dishadudhal/performanceevaluation-of-sdn-controllers-using-cbench-and-iperf-e9296f63115c (accessed Apr. 30, 2023).; R. Kumar, M. Atulkar, and N. Kumar, Performance Comparison of Ryu and Floodlight Controllers in Different SDN Topologies. 2019.; R. Ramadhan, N. Armi, R. Magdalena, G. N. Nurkahfi, and M. M. M. Dinata, “QoS Performance of Software Define Network Using Open Network Operating System Controller,” in Proceeding - 2020 International Conference on Radar, Antenna, Microwave, Electronics and Telecommunications, ICRAMET 2020, Institute of Electrical and Electronics Engineers Inc., Nov. 2020, pp. 124–128. doi:10.1109/ICRAMET51080.2020.9298662.; M. Z. Abdullah, N. A. Al-Awad, and F. W. Hussein, “Evaluating and Comparing the Performance of Using Multiple Controllers in Software Defined Networks,” Modern Education and Computer Science, vol. 8, pp. 27–34, 2019, doi:10.5815/ijmecs.2019.08.03.; A. Singh, N. Kaur, and H. Kaur, “Extensive performance analysis of OpenDayLight (ODL) and Open Network Operating System (ONOS) SDN controllers,” 2022, doi:10.1016/j.micpro.2022.104715.; “SDN Framework RYU Using OpenFlow 1.3 RYU project team”.; “ONOS - ONOS - Wiki.” https://wiki.onosproject.org/ (accessed Sep. 07, 2023).; H. Facchini, S. Perez, R. Blanchet, B. Roberti, and R. Azcarate, “Experimental performance contrast between SDN and traditional networks,” in 2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2021, Institute of Electrical and Electronics Engineers Inc., 2021. doi:10.1109/CHILECON54041.2021.9702982.; D. Bombal, “GNS3,” 2015. https://gns3.com/sdn-101-mininet-openflow-and-gns (accessed Sep. 07, 2023).; “OpenFlow.” https://wiki.wireshark.org/OpenFlow (accessed Sep. 08, 2023).; J. Mogul and S. Deering, “RFC 1191 - Path MTU discovery.” https://datatracker.ietf.org/doc/html/rfc1191 (accessed Sep. 07, 2023).; “Rendimiento del servicio de volumen en bloque.” https://docs.oracle.com/esww/iaas/Content/Block/Concepts/blockvolumeperformance.htm (accessed Sep. 07, 2023).; “Data Center Switches – Cisco Nexus - Cisco.” https://www.cisco.com/site/us/en/products/networking/cloud-networkingswitches/index.html (accessed Sep. 07, 2023).; “muestra la memoria virtual del sistema %7C Juniper Networks.” https://www.juniper.net/documentation/mx/es/software/junos/junos-overview/topics/ref/command/show-system-virtual-memory.html (accessed Sep. 07, 2023).; “Why Move to a Modern Network Operating System? White Paper - Cisco.” https://www.cisco.com/c/en/us/products/collateral/ios-nx-os-software/ios-xrsoftware/white-paper-c11-744829.html (accessed Sep. 04, 2023).; “Software-Defined Networking (SDN) Definition - Open Networking Foundation.” https://opennetworking.org/sdn-definition/ (accessed Sep. 03, 2023).; “threading — Thread-based parallelism — Python 3.11.5 documentation.” https://docs.python.org/3/library/threading.html (accessed Sep. 05, 2023).; 5gamericas, “5gamericas: Statistics - Latin America.” [Online]. Available: http://www.5gamericas.org/en/resources/statistics/statistics-latin-america/.; A. Navarro Cadavid, A. Arteaga, L. Vargas, J. Renteria, and M. Arciniegas, “Spectrum Monitoring System and Benchmarking of Mobile Networks Using Open Software Radios SIMONES,” IEEE Lat. Am. Trans., vol. 13, no. 11, pp. 3592–3597, 2015.; M. Iedema and H. Samra, Getting Started with OpenBTS. 2015.; A. Dubey, D. Vohra, K. Vachhani, and A. Rao, “Demonstration of vulnerabilities in GSM security with USRP B200 and open-source penetration tools,” in Proceedings - AsiaPacific Conference on Communications, APCC 2016, 2016, pp. 496–501.; B. Harmat et al., “The Security Implications of IMSI Catchers,” in International Conference on Security and Management (SAM’15), 2015, pp. 57–62.; Mesud Hadžialić; Mirko Škrbić; Kemal Huseinović; Irvin Kočan; Jasmin Mušović, “An Approach to Analyze Security of GSM Network,” 22nd Telecommun. forum TELFOR 2014, 2014.; S. Ghafoor, K. N. Brown, and C. J. Sreenan, “Experimental evaluation of a software defined radio-based prototype for a disaster response cellular network,” in Proceedings of the 2015 2nd International Conference on Information and Communication Technologies for Disaster Management, ICT-DM 2015, 2016, pp. 57–63.; K. Guevara, M. Rodriguez, N. Gallo, G. Velasco, K. Vasudeva, and I. Guvenc, “UAVbased GSM network for public safety communications,” in Conference Proceedings - IEEE SOUTHEASTCON, 2015, vol. 2015-June, no. June.; T. Di. Putri and T. Juhana, “Mobile-openbts implementation of natural disaster victims search,” in Proceedings - ICWT 2017: 3rd International Conference on Wireless and Telematics 2017, 2018, vol. 2017-July, pp. 149–154.; J. Mpala and G. Van Stam, “Open BTS, a GSM experiment in rural Zambia,” Africomm, Yaounde, Cameroon, pp. 1–9, 2012.; M. Zheleva, A. Paul, D. L. Johnson, and E. Belding, “Kwiizya: Local Cellular Network Services in Remote Areas,” in MobiSys, 2013, July, p. 417.; L. Angrisani, P. Daponte, and M. D'Apuzzo, “A measurement method based on time-frequency representations for testing GSM equipment,” IEEE Trans. Instrum. Meas., vol. 49, no. 5, pp. 1050–1056, 2000.; A. Aiello and D. Grimaldi, “Frequency error measurement in GMSK signals in a multipath propagation environment,” IEEE Trans. Instrum. Meas., vol. 52, no. 3, pp. 938–945, 2003.; K. Paul, “Introduction to GSM and GSM mobile RF transceiver derivation.; Union Internacional de Telecomunicaciones., “Definiciones de sistema radioeléctrico determinado por programas informáticos (RDI) y sistema radioeléctrico cognoscitivo (SRC),” vol. 2152, 2009.; T. ETSI Specification, “Digital cellular telecomm mmunications system (Phase e 2+) (GSM); GSM/EDGE Multiplexing and multiple access on the radio path (3GPP TS 45.0.002 version 13.3.1 Release 13).”; J. M. HUIDOBRO, Comunicaciones móviles: sistemas GSM, UMTS Y LTE, 2012th ed.; ETSI, Digital cellular telecommunications system (Phase 2+); Release independent frequency bands; Implementation guidelines (3GPP TS 05.14 version 7.2.0 Release 1998), vol. 0. 2001, pp. 0–31.; ETSI, Digital cellular telecommunications system (Phase 2+); Radio transmission and reception (3GPP TS 45.005 version 12.4.0 Release 12), vol. 0. 2008, pp. 0–40.; T. Specification, “ETSI TS 145 002,” vol. 0, pp. 0–112, 2014.; T. ETSI Specification, Technical Specification Group GSM/EDGE Radio Access Network; Digital cellular telecommunications system (Phase 2+); Modulation TS 05.04, vol. 0. 2003, pp. 1–28.; 3GPP, 3rd Generation Partnership Project; Technical Specification Group GSM/EDGE Radio Access Network; Digital cellular telecommunications system (Phase 2+); Radio subsystem synchronization. 1999.; ETSI, Digital cellular telecommunications system (Phase 2 and Phase 2+); Base Station System (BSS) equipment specification; Radio aspects (3GPP TS 11.21 version 8.6.0 Release 1999), vol. 0. 2008, pp. 0–40.; ETSI, EN 300 910 Digital cellular telecommunications system (Phase 2+); Radio transmission and reception (GSM 05.05 version 8.5.1 Release 1999), vol. 1. 1999, pp. 1– 10.; Keysight Technologies, “Understanding GSM/EDGE Transmitter and Receiver Measurements for Base Transceiver Stations and their Components.”; E. No. O. . U. S. A. Gbadamosi A. M. Aibinu, “Towards Independent Measurement of End to End Bit Error Rate in GSM Network,” pp. 1–4, 2014.; R. Communications, “Laboratory works in Radio Communications GSM Transceiver Measurements.” Prentice-Hall Inc, 1995.; T. ETSI Specification, 3GPP TS 05.05 3rd Generation Partnership Project; Technical Specification Group GSM/EDGE Radio Access Network; Radio transmission and reception, vol. 0. 2005.; E. Research, “USRP Hardware Driver and USRP Manual Version: 003.010.001.001-41- g6abf277.” [Online]. Available: http://openbts.org/hardware/.; R. Networks, C. C. Attribution-sharealike, and U. License, “OpenBTS Application Suite,” 2014; Agilent Technologies, “Making the Phase and Frequency Error Measurement.” [Online]. Available: http://literature.cdn.keysight.com/litweb/pdf/ads2001/vsaedgemeas/gsmmeas6.html.; D. Seidl et al., «The multiparameter station at Galeras Volcano (Colombia): concept and realization», Journal of Volcanology and Geothermal Research, vol. 125, n.o 1-2, pp. 1-12, 2003, doi:10.1016/s0377-0273(03)00075-1.; J. M, «Review of electric and magnetic fields accompanying seismic and volcanic activity», U.S. Geological Survey, vol. 18, n.o 5, pp. 441-475, 1997, doi:10.1023/A:1006500408086.; V. Surkov y V. Pilipenko, «Estimate of ULF electromagnetic noise caused by a fluid flow during seismic or volcano activity», Copernicus Publications, vol. 2, n.o 10, pp. 6475-6497, 2014, doi:10.5194/nhessd-2-6475-2014.; Y. Sasai et al., «Magnetic and electric field observations during the 2000 activity of Miyakejima volcano, Central Japan», Earth and Planetary Science Letters, vol. 203, n.o 2, pp. 769-777, 2002, doi:10.1016/S0012-821X(02)00857-9.; M. Valenciano, «Implementación de un radioenlace LPWAN con tecnología LoRa», Tesis, Universidad de Valladolid, Valladolid, 2022. [En línea]. Disponible en: https://uvadoc.uva.es/bitstream/handle/10324/57458/TFGG5892.pdf?sequence=1&isAllowed=y; R. Piyare, A. Murphy, M. Magno, y L. Benini, «On-Demand LoRa: Asynchronous TDMA for EnergyEfficient and Low Latency Communication in IoT», Sensors, vol. 18, n.o 3718, 2018, doi:10.3390/s18113718.; C. Guerrero, «Evaluación de los retardos en redes LoRaWAN multisalto con topología lineal», Tesis, Universidad Politécnica Nacional, Quito Ecuador, 2022.; H. Mahmood Jawad, R. Nordin, S. Kamel Gharghan, A. Mahmood Jawad, y Mahamod Ismail, «Energy-efficient wireless sensor networks for precision agriculture: A review», Sensors, vol. 17, n.o 8, p. 1781, 2017, doi:10.3390/s17081781.; R. Muñoz, «Modelado y evaluación de la eficiencia del estándar SCHC para el transporte de paquetes IP sobre LoRaWAN», Tesis Maestría, Universidad de Chile, Santiago de Chile, 2020. [En línea]. Disponible en: https://repositorio.uchile.cl/bitstream/handle/2250/177977/Modelado-y-evaluacion-de-laeficiencia-del-estandar-SCHC-para-el-transporte-de-paquetes-IP.pdf?sequence=1; W. Yong, L. Minzan, y Z. Man, «Remote-control system for greenhouse based on opensource hardware», IFAC, vol. 52, n.o 30, pp. 178-183, 2019, doi:10.1016/j.ifacol.2019.12.518.; L. Cilleruelo and A. Zubiaga, “Una aproximación a la Educación STEAM. Prácticas educativas en la encrucijada arte, ciencia y tecnología. Jornadas de Psicodidáctica, 18.,” 2014.; M. L. Matute Sánchez and C. R. Contreras Alvarado, “Diseño y desarrollo de un asistente robótico basado en sistemas embebidos y aplicaciones móviles como herramienta de soporte pedagógica para niños de uno a cinco años,” 2019.; E. Systems, “ESP8266EX,” 2023.; K. Arakadakis, P. Charalampidis, A. Makrogiannakis, and A. Fragkiadakis, “Firmware Over-the-air Programming Techniques for IoT Networks-A Survey,” ACM Comput. Surv., vol. 54, no. 9, pp. 1–24, 2022, doi:10.1145/3472292.; I. G. Juan, I. Garc, I. F. Milena, and I. G. Ezequiel, “Gestión de Redes Centralizado desde GNU / Linux,” Cordoba, 2021.; Y. T. Chávez Cujilán and J. M. Espinoza Ortíz, “Desarrollo de una plataforma web para el control y seguimiento de productos terminados en la empresa camaronera ambartex s.a. empleando la metodología kanban,” Universidad de Guayaquil, 2016.; M. docs Web, “Métodos de petición HTTP,” 2023. https://developer.mozilla.org/es/docs/Web/HTTP/Methods.; R. Pereira, C. de Souza, D. Patino, and J. Lata, “Platform for Distance Learning of Microcontrollers and Internet of Things; [Plataforma De Enseñanza a Distancia De Microcontroladores E Internet De Las Cosas],” Ingenius, vol. 2022, no. 28, pp. 53 – 62, 2022, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85144095611&doi=10.17163%2Fings.n28.2022.05&partnerID=40&md5=cc9fd40b5b28 c66ac89ebf8f68ab3275.; M. Garduno-Aparicio, J. Rodriguez-Resendiz, G. Macias-Bobadilla, and S. Thenozhi, “A Multidisciplinary Industrial Robot Approach for Teaching Mechatronics-Related Courses,” IEEE Trans. Educ., vol. 61, no. 1, pp. 55–62, 2018, doi:10.1109/TE.2017.2741446.; P. Jacko et al., “Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips,” Sensors, vol. 22, no. 4, 2022, doi:10.3390/s22041440.; Ð. Mijailović, A. Ðorđdević, M. Stefanovic, D. Vidojević, A. Gazizulina, and D. Projović, “A cloud-based with microcontroller platforms system designed to educate students within digitalization and the industry 4.0 paradigm,” Sustain., vol. 13, no. 22, 2021, doi:10.3390/su132212396.; J. Vega D, “Soporte para gestión remota ota sobre una picocelda GSM / GPRS OverThe-Air management on a GSM / GPRS picocell Graduado en Ingeniería de Tecnologías de Telecomunicación,” Universidad de Cantabria, 2014.; J. Molnár et al., “Weather Station IoT Educational Model Using Cloud Services,” JUCS - J. Univers. Comput. Sci., vol. 26, no. 11, pp. 1495–1512, Nov. 28AD, [Online]. Available: https://doi.org/10.3897/jucs.2020.079.; O. Velihorskyi, I. Nesterov, and M. Khomenko, “Remote Debugging of Embedded Systems in Stm32Cubemonitor,” pp. 22–25, 2020, doi:10.35598/mcfpga.2020.007.; G. Zhabelova, M. Vesterlund, S. Eschmann, Y. Berezovskaya, V. Vyatkin, and D. Flieller, “A Comprehensive Model of Data Center: From CPU to Cooling Tower,” IEEE Access, vol. 6, pp. 61254–61266, 2018, doi:10.1109/ACCESS.2018.2875623.; I. Marín, “un enfoque de neurociencia sobre la participación de los estudiantes en las clases de microcontroladores durante la pandemia covid19,” in 14a Conferencia Internacional Anual de Educación, Investigación e Innovación Actas JA - ICERI2021, pp. 5776-5783 urgencias-, doi:10.21125/iceri.2021.1303 Año anual - 2021.; S. P. De Araujo and L. Dias Souza, “STEAM Education y el Diseño de los modelos de aprendizaje MOE, TAS y COM,” i+Diseño. Rev. Científico-Académica Int. Innovación, Investig. y Desarro. en Diseño, vol. 17, pp. 23–34, 2022, doi:10.24310/idiseno.2022.v17i.15683.; E. Flores, “Ingenieria de Software,” 2021. https://ingenieriadesoftware.mex.tl/52666_Presentacion.html.; E. Inga, J. Inga, and A. Ortega, “Novel approach sizing and routing of wireless sensor networks for applications in smart cities,” Sensors, vol. 21, no. 14, pp. 1–17, 2021, doi:10.3390/s21144692.; T. Vince et al., “IoT implementation in remote measuring laboratory VMLab analyses,” J. Univers. Comput. Sci., vol. 26, no. 11, pp. 1402–1421, 2020, doi:10.3897/jucs.2020.074.; I. Olarte C and L. A. Rodriguez Umaña, “diseño de arquitectura estándar para la adquisición y transmisión de datos integrados en la automatización de cultivos acuaponicos,” Universidad Cooperativa de Colombia, 2022.; J. I. Vega Luna, F. J. Sánchez-Rangel, G. Salgado-Guzmán, J. F. Cosme-Aceves, V. N. Tapia-Vargas, and M. A. Lagos-Acosta, “Red de monitorización para automatizar el sistema de enfriamiento de un centro de datos,” Ingenius, no. 24, pp. 87–96, 2020, doi:10.17163/ings.n24.2020.09.; M. Rodríguez, S. Zafra y S. Ortega, «La revisión sistemática de la literatura científica y la necesidad de visualizar los resultados de las investigaciones.,» Revista Logos, Ciencia & Tecnología, vol. 7, nº 1, pp. 101-103, 2015.; M. Salcido, A. del Toro, N. Medina, F. RamÍrez, M. Gacia, A. Briceño y J. Jiménez, «Revisión sistemática: el más alto nivel de evidencia,» Orthotips AMOT, vol. 17, nº 4, pp. 217-22%7C, 2021.; B. Moreno, M. Muñoz, J. Cuellar, S. Domancic y J. Villanueva, «Revisiones Sistemáticas: definición y nociones básicas.,» Revista clínica de periodoncia, implantología y rehabilitación oral, vol. 11, nº 3, pp. 184-186, 2018.; C. Ierandi, L. Orihuela, I. Jurado, Á. Rodríguez Del Nozal y A. Tapia, «Revisión sistemática de la literatura en ingeniería de sistemas. Caso práctico: técnicas de estimación distribuida de sistemas ciberfísicos.,» Actas de las XXXVIII Jornadas de Automática, pp. 84-91, 2017.; H. García, «Conceptos fundamentales de las revisiones sistemáticas/metaanálisis.,» Urología colombiana, vol. 24, nº 1, pp. 28-34, 2015.; O. Beltrán, «Revisiones sistemáticas de la literatura.,» Revista colombiana de gastroenterología., vol. 20, nº 1, pp. 60-69, 2005.; C. Manterola, P. Astudillo, E. Arias y N. Claros, «Revisiones sistemáticas de la literatura. Qué se debe saber acerca de ellas.,» Cirugía española, vol. 91, nº 3, pp. 149-155, 2023.; L. Letelier, J. Manríquez y G. Rada, «Revisiones sistemáticas y metaanálisis:¿ son la mejor evidencia?,» Revista médica de Chile, vol. 133, nº 2, pp. 246-249, 2005.; OpenAI, «ChatGPT (Versión del 16 de octubre de 2023),» 2023. [En línea]. Available: https://chat.openai.com/.; G. Guevara, A. Verdesoto, S. Guevara y E. González, «Las Tecnologías de la Información y la Comunicación en la educación universitaria,» Revista Científica de Investigación actualización del mundo de las Ciencias, vol. 3, nº 3, pp. 409-422, 2019.; J. Cobo, «El concepto de tecnologías de la información. Benchmarking sobre las definiciones de las TIC en la sociedad del conocimiento.,» Revista de Estudios de Comunicación, vol. 14, nº 27, pp. 295-318, 2009.; Z. L. C. A. P. G. L. V. C. &. D. C. M. B. Aliaga, «Software educativo para favorecer la aprehensión de los contenidos de ingeniería de software,» Revista de Investigación en Tecnologías de la Información, pp. 5(9), 63-69., 2017.; B. Gros, El ordenador invisible. Hacia la apropiación del ordenador en la enseñanza, Barcelona, España: Editorial Gedisa, 2000.; S. Kumar, «Knowledge of software education,» Global Research Journal of Educaion, pp. 1-2, 2022.; H. Rosario N, «TIC EN AMBIENTES EDUCATIVOS,» Comunidad y Salud, vol. 5, nº 2, 2007.; ] U. IIEP, «Tecnologías de la información y la comunicación (TICs) en la educación,» IIEP Learning Portal, 22 Marzo 2023. [En línea]. Available: https://learningportal.iiep.unesco.org/es/fichas-praticas/mejorar-elaprendizaje/tecnologias-de-la-informacion-y-la-comunicacion-tics-en-la. [Último acceso: 5 Octubre 2023].; D. Correa y F. Pérez, «Los modelos pedagógicos: trayectos históricos,» Debates por la Historia., pp. 125-154, 2022.; B. Joyce y M. Weil, Los modelos de enseñanza., Madrid, España: Editorial Anaya, 1985.; F. García, «Los modelos didácticos como instrumento de análisis y de intervención en la realidad educativa.,» García Pérez, F. F. (2000). Los modelos didácticos como instrumento de análiBiblio 3w: Revista Bibliográfica de Geografía y Ciencias Sociales., pp. 1-12, 2000.; V. Niño, Metodología de la investigación. Diseño y ejecución., Bogotá, Colombia: Ediciones de la U, 2011.; G. Fidias, El proyecto de Investigación. Introducción a la metodología científica., Caracas, Venezuela: Editorial Episteme, CA., 2006.; L. Larriba, «La investigación de los modelos didácticos y de las estrategias de enseñanza.,» Enseñanza., pp. 73-88, 2001.; N. Romero y J. Moncada, «Modelo didáctico para la enseñanzade la educación ambiental en la Educación Superior Venezolana,» Revista de Pedagogía, pp. 443-476, 2007.; A. Brolpito, Digital Skills and Competence, and Digital and Online Learning., European Training Foundation., 2018.; O. Najar, «Tecnologías de la información y la comunicación aplicadas a la educación,» Praxis y Saber, vol. 7, nº 14, pp. 9-16, 2016.; E. Kispeter, What digital skills do adults need to succeed in the workplace now and in the next 10 years., Warwick Institute for Employement Research., 2018.; A. Gargallo, «La integración de las TIC en los procesos educativos y organizativos.,» Educar em Revista., vol. 34, nº 69, pp. 325-339, 2018.; J. Cabrero, Tecnología educativa. Diseño y utilización de medios en la enseñanza., Barcelona, España: Editorial Paidos, 2001.; L. Alvarez, Modelos de gestión, Bogotá: Fundación Universitaria del Área Andina, 2017.; T. Huertas, E. Suárez, M. Salgado, L. Jadán y B. Jiménez, «Diseño de un modelo de gestión. Base científica y práctica para su elaboración.,» Revista Universidad y Sociedad, 12(1), 165-177., vol. 12, nº 1, pp. 165-177, 2020.; L. Reginato, C. Pereira y R. Guerreiro, «Una investigacion sobre las caracteristicas del modelo de gestion: un estudio de caso.,» Reginato, L., Pereira, C. A., & Guerreiro, R. (2009). Una investigacion sobre las cara Iberoamerican journal of industrial engineering, vol. 1, nº 1, pp. 24-45, 2009.; L. Angulo, Gestión de ptoyectos. Bajo el enfoque del PMBOK, Lima: Editorial Macro, 215.; A. López y D. Lankenau, Administración de proyectos. La clave para la coordinación efectiva de actividades y recursos, México: Pearson, 2017.; R. Terrazas, «Modelo conceptual para la gestión de proyectos.,» Perspectivas, vol. 24, pp. 165-188, 2009.; A. Narvaez y R. Esperanza, «Modelos para la Gestión de Proyectos.,» Informador Técnico, vol. 71, pp. 53-58, 2007.; U. IIEP, «Tecnologías de la información y la comunicación (TICs) en la educación,» IIEP Learning Portal, 22 Marzo 2023. [En línea]. Available: https://learningportal.iiep.unesco.org/es/fichas-praticas/mejorar-elaprendizaje/tecnologias-de-la-informacion-y-la-comunicacion-tics-en-la. [Último acceso: 5 Octubre 2023].; J. A. Pineda Acero, «Diseño de proyectos educativos mediados por TIC: un marco de referencia,» Opción, vol. 32, nº 10, pp. 479-499, 2016.; UNESCO, Herramientas para la gestión de proyectos educativos con TIC, Buenos Aires: UNESCO, 2007.; E. H. Legresti, «Proyecto de incorporación de las TICs como herramienta de aprendizaje,» 2019.; D. &. C. S. L. Alan Neill, Procesos y fundamentos de la investigación científica. , 53(9)., Macha, Ecuador: Ediciones UTMACH, 2018.; A. Carli, La Ciencia como herramienta. Guía para la investigación y la realización de informes, monografías y tesis científicas., Buenos Aires: Editorial Biblos, 2008.; P. Suárez, Metodología de la investigación. Diseño y técnicas, Bogotá, Colombia: Orión Editores Ltda., 2004.; M. Medina, La investigación aplicada a proyectos. Identificación del proyecto y formulación de la investigación., Bogotá, Colombia: Ediciones Ántropos Ltda., 2007.; Aplicación y uso de drones: https://edu.gcfglobal.org/es/cultura-tecnologica/quees-un-dron-y-cuales-son-sus-usos/1/; Como funciona el Mapeo a partir de drones? : https://ts2.space/es/como-funcionael-sistema-de-mapeo-3d-de-un-dron/; Duarte, J. F., Galindo Gómez, S. F., Rodríguez Pupo, S., PayánDurán, L. F., & Velásquez-Rodrígue, C. E. (2022). Paso a paso para desarrollar innovaciones sociales. Documento Técnico del PCIS.; Hoyos Montoya, E. A., & de Souza Bías, E. (2021). [Título del artículo]. Recuperado dehttps://doi.org/10.22490/25394088.5609; UN (2022). Objetivos de Desarrollo Sosteninle Tomado de: https://www.un.org/sustainabledevelopment/es/waterand-sanitation/; MEN( 2022) titulado ORIENTACIONES CURRICULARES PARA EL ÁREA DETECNOLOGÍA E INFORMÁTICA EN LA EDUCACIÓN BÁSICA Y MEDIA https://www.colombiaaprende.edu.co/sites/default/files/files_public/2022- 11/Orientaciones_Curricures_Tecnologia.pdf; Secretaría de Ambiente. Bogotá está mejorando y en el Día Mundial de los Humedales reafirma su compromiso con estos ecosistemas. https://www.ambientebogota.gov.co/ (2022).; Cuellar, Y., Pérez, L. Modelado multitemporal y simulación de la dinámica compleja en humedales urbanos: el caso de Bogotá, Colombia. Representante científico 13 , 9374 (2023).https://doi.org/10.1038/s41598-023-36600-8; Ramsar. "Humedales urbanos: tierras preciadas, no terrenos baldíos ". https://www.ramsar.org/resources/publications (2018).; Das, N. y Mehrotra, S. Humedales en contextos urbanos: un caso de Bhoj Wetland. En 2021 Simposio internacional de geociencia y teledetección del IEEE IGARSS (págs. 6972-6975). IEEE(2021).; Van der Hammen, T. Los humedales de la Sabana: origen, evolución, degradación y restauración. en Los humedales de Bogotá y la Sabana, Conservación Internacional 19–51(2003).; Ramsar (2021). " Transformar la agricultura para sostener a las personas y mantener los humedales”. Tomado de: https://www.ramsar.org/sites/default/files/documents/library/rpb6_agriculture_s. pdf; Espínola Pérez, A. M. (2014). Clasificación de Imágenes de Satélite mediante AutómatasCelulares (Tesis doctoral). Universidad de Almería. Dirigida por Dr. D. Luis F. Iribarne Martínez, Dra. Dña. Rosa M. Ayala Palenzuela, y Dr. D. José Antonio Piedra Fernández.; He, W., Chen, S., Liu, X., & Chen, J. (2008). Water quality monitoring in a slightly-pollutedinland water body through remote sensing — Case study of the Guanting Reservoir in Beijing, China. Frontiers of Environmental Science & Engineering in China, 2, 163–171.; Carbonell Carrera, C., & Bermejo Asensio, L. A. (2017). Augmented reality as a digital teaching environment to develop spatial thinking. Cartography and Geographic Information Science, 44(3), 259-270. https://doi.org/10.1080/15230406.2016.1145556; Cuellar, Y., & Perez, L. (2023). Multitemporal modeling and simulation of the complex dynamics in urban wetlands: the case of Bogota, Colombia. Scientific Reports, 13, 9374.; Carbonell Carrera, C., & Bermejo Asensio, L. A. (2017). Augmented reality as a digital teachingenvironment to develop spatial thinking. Cartography and Geographic Information Science, 44(3), 259-270. https://doi.org/10.1080/15230406.2016.1145556; Alikhani, S., Nummi, P. & Ojala, A. Humedales urbanos: una revisión de los valores ecológicosy culturales. Agua 13 , 3301 (2021).; H. Mohapatra and S. I. Hosain, “Intermodal dispersion free few-mode (quadruple mode) fiber: A theoretical modelling,” Opt Commun, vol. 305, pp. 267–270, 2013, doi:10.1016/j.optcom.2013.05.018.; J. Tu, K. Long, and K. Saitoh, “Design and optimization of 3-mode×12-core dual-ring structured few-mode multi-core fiber,” Opt Commun, vol. 381, pp. 30–36, 2016, doi:10.1016/j.optcom.2016.06.049.; H. Zhu, Z. Cao, and Q. Shen, “Construction of the refractive index profiles for few-mode planar optical waveguides,” Opt Commun, vol. 260, no. 2, pp. 542–547, 2006, doi:10.1016/j.optcom.2005.11.011.; G. F. Fibers, H. Mohapatra, and S. I. Hosain, “Variational Approximations for LP l 1 Modes,” vol. 26, no. 4, pp. 372–375, 2014.; F. Ferreira, D. Fonseca, and H. Silva, “Design of few-mode fibers with up to 12 modes and low differential mode delay,” International Conference on Transparent Optical Networks, vol. 32, no. 3, pp. 353–360, 2014, doi:10.1109/ICTON.2014.6876696.; A. Rjeb, H. Seleem, H. Fathallah, and M. Machhout, “Design of 12 OAM-Graded index few mode fi bers for next generation short haul interconnect transmission,” Optical Fiber Technology, vol. 55, no. October 2019, p. 102148, 2020, doi:10.1016/j.yofte.2020.102148.; H. Kubota and T. Morioka, “Few-mode optical fiber for mode-division multiplexing,” Optical Fiber Technology, vol. 17, no. 5, pp. 490–494, 2011, doi:10.1016/j.yofte.2011.06.011.; J. Zhang and L. Mao, “Integrating multiple transportation modes into measures of spatial food accessibility,” J Transp Health, vol. 13, no. March, pp. 1–11, 2019, doi:10.1016/j.jth.2019.03.001.; A. E. Zhukov, V. A. Burdin, and A. V Bourdine, “Design of silica optical fibers with enlarged core diameter for a few-mode fiber optic links of onboard and industrial multiGigabit networks,” Procedia Eng, vol. 201, pp. 105–116, 2017, doi:10.1016/j.proeng.2017.09.675.; W. Jin et al., “Few-mode and large-mode-area fiber with circularly distributed cores,” Opt Commun, vol. 387, no. July 2016, pp. 79–83, 2017, doi:10.1016/j.optcom.2016.11.016.; J. Han and C. Qu, “Characterization of distributed mode crosstalk in few-mode fiber links with low MIMO complexity,” Physical Communication, vol. 25, pp. 310–314, 2017, doi:10.1016/j.phycom.2017.02.002.; S. Wei-Hua, X. Chuan-Xiang, and Y. Jing, “A new type of Few-mode Photonic Crystal Fiber with nearly-zero flattened Dispersion properties,” ICOCN 2017 - 16th International Conference on Optical Communications and Networks, vol. 2017-Novem, pp. 16–18, 2017, doi:10.1109/icocn.2017.8374406.; R. Miyazaki, M. Ohashi, H. Kubota, Y. Miyoshi, and N. Shibata, “Chromatic dispersion measurement of the high order mode in a few-mode fiber using an interferometric technique and a mode converter,” 2017 Opto-Electronics and Communications Conference, OECC 2017 and Photonics Global Conference, PGC 2017, vol. 2017- Novem, pp. 1–3, 2017, doi:10.1109/OECC.2017.8114866.; A. Marcos Aparicio, “Cable submarino, conexión DWDM entre continentes,” Sistema de Gestión de incidencias Open Source, 2017, [Online]. Available: http://oa.upm.es/48560/1/PFC_ANA_ISABEL_MARCOS_APARICIO.pdf; G. P. (Govind P. ) Agrawal, Fiber-optic communication systems. Wiley-Interscience, 2002.; S. Matthew, Elementos de electromagnetismo. 2009. doi: 10: 0-8400-5444-0.; D. Pozar, “Microwave Engineering 2nd Ed David Pozar,” pp. 1–736, 2008, [Online]. Available: papers2://publication/uuid/74B11176-09A2-4077-9BDE-1E89002D0735; R. Neri Vela and L. H. Porragas Beltrán, Líneas de transmisión, vol. 3, no. 2. 2012. doi:10.25009/uv.1998.124.; D. Gloge and E. A. J. Marcatili, “Multimode Theory of Graded-Core Fibers,” 1973.; M. Carmen. España Booquera, Comunicaciones ópticas : conceptos esenciales y resolución de ejercicios. Díaz de Santos, 2005. Accessed: Sep. 25, 2023. [Online]. Available: https://www.academia.edu/33300228/MAR%C3%8DA_CARMEN_ESPA%C3%91A_B OQUERA_COMUNICACIONES_%C3%93PTICAS_Conceptos_esenciales_y_resoluci %C3%B3n_de_ejercicios; K. Gomez, L. Goratti, F. Granelli, y T. Rasheed, «A Comparative Study of Scheduling Disciplines in 5G Systems for Emergency Communications», presentado en 1st International Conference on 5G for Ubiquitous Connectivity, Levi, Finland, 2014. doi:10.4108/icst.5gu.2014.257987.; K. Pedersen, G. Pocovi, J. Steiner, y A. Maeder, «Agile 5G Scheduler for Improved E2E Performance and Flexibility for Different Network Implementations», IEEE Commun. Mag., vol. 56, n.o 3, pp. 210-217, mar. 2018, doi:10.1109/MCOM.2017.1700517.; A. Akhtar y H. Arslan, «Downlink resource allocation and packet scheduling in multinumerology wireless systems», en 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Barcelona, abr. 2018, pp. 362-367. doi:10.1109/WCNCW.2018.8369012.; K. I. Pedersen, M. Niparko, J. Steiner, J. Oszmianski, L. Mudolo, y S. R. Khosravirad, «System Level Analysis of Dynamic User-Centric Scheduling for a Flexible 5G Design», en 2016 IEEE Global Communications Conference (GLOBECOM), Washington, DC, USA, dic. 2016, pp. 1-6. doi:10.1109/GLOCOM.2016.7842312.; S. A. AlQahtani and M. Alhassany, “Comparing different LTE scheduling schemes,” in 2013 9th international wireless communications and mobile computing conference (IWCMC), 2013, pp. 264–269.; T. Dikamba, “Downlink scheduling in 3GPP long term evolution (LTE),” 2011.; S. V. S. Prakash and M. Visali, “On demand SINR based scheduling algorithm (ODSSA) for mobile uplink communication in LTE networks,” in 2015 International Conference on Signal Processing and Communication Engineering Systems, 2015, pp. 453–457.; G. Muñoz, I. H. Solana, and M. Ángela, “Gestión de Recursos Radio en Redes Móviles Celulares Basadas en Tecnología OFDMA para la Provisión de QoS y Control de la Interferencia.”; C. So-In, R. Jain, y A. K. Tamimi, “A Deficit Round Robin with Fragmentation scheduler for IEEE 802.16e Mobile WiMAX”, en IEEE Sarnoff Symposium, 2009. SARNOFF ’09, 2009, pp. 1–7.; H. Fattah y C. Leung, “An Improved Round Robin Packet Scheduler for Wireless Networks”, International Journal of Wireless Information Networks, vol. 11, pp. 41–54, 2004.; J. Vihriala et al., «Numerology and frame structure for 5G radio access», en 2016 IEEE 27th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications; N. Siasi, A. Jaesim, A. Aldalbahi, y N. Ghani, «Link Failure Recovery in NFV for 5G and Beyond», en 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Barcelona, Spain, oct. 2019, pp. 144-148. doi:10.1109/WiMOB.2019.8923413.; D.-H. Kim, B.-H. Ryu, y C.-G. Kang, «Packet Scheduling Algorithm Considering a Minimum Bit Rate for Non-realtime Traffic in an OFDMA/FDD-Based Mobile Internet Access System», ETRI J., vol. 26, n.o 1, pp. 48-52, feb. 2004, doi:10.4218/etrij.04.0203.0005.; M. Yan, G. Feng, J. Zhou, Y. Sun, y Y.-C. Liang, «Intelligent Resource Scheduling for 5G Radio Access Network Slicing», IEEE Trans. Veh. Technol., vol. 68, n.o 8, pp. 7691- 7703, ago. 2019, doi:10.1109/TVT.2019.2922668.; A. A. Esswie y K. I. Pedersen, «Opportunistic Spatial Preemptive Scheduling for URLLC and eMBB Coexistence in Multi-User 5G Networks», IEEE Access, vol. 6, pp. 38451-38463, 2018, doi:10.1109/ACCESS.2018.2854292.; R. B. Abreu, G. Pocovi, T. H. Jacobsen, M. Centenaro, K. I. Pedersen, y T. E. Kolding, «Scheduling Enhancements and Performance Evaluation of Downlink 5G TimeSensitive Communications», IEEE Access, vol. 8, pp. 128106-128115, 2020, doi:10.1109/ACCESS.2020.3008598.; Z. Gu et al., «Knowledge-Assisted Deep Reinforcement Learning in 5G Scheduler Design: From Theoretical Framework to Implementation», ArXiv200908346 Cs Eess, feb. 2021, Accedido: feb. 06, 2021. [En línea]. Disponible en: http://arxiv.org/abs/2009.08346; Khaira, M. S., & Borkar, N. Y., «U.S. Patent No. 5,357,512. Washington, DC: U.S. Patent and Trademark Office.» 1994.; C. J. Katila, C. Buratti, M. D. Abrignani, y R. Verdone, «Neighbors-Aware Proportional Fair scheduling for future wireless networks with mixed MAC protocols», EURASIP J. Wirel. Commun. Netw., vol. 2017, n.o 1, p. 93, dic. 2017, doi:10.1186/s13638-017- 0875-6.; Humaira Rashid Khan, Fahd Sikandar Khan, Ahmed Shuja Syed, Javeed Akhtar, Chapter 27 - Nano-inks and their applications in packaging industries, Editor(s): Ram K. Gupta, Tuan Anh Nguyen, In Micro and Nano Technologies, Smart Multifunctional Nano-inks, Elsevier, 2023, Pages 687-698, ISBN 9780323911450, https://doi.org/10.1016/B978-0-323-91145-0.00015-3.; Muhammad Ifaz Shahriar Chowdhury, Yashdi Saif Autul, Sazedur Rahman, Md Enamul Hoque, 11 - Polymer nanocomposites for automotive applications, Editor(s): Md Enamul Hoque, Kumar Ramar, Ahmed Sharif, In Woodhead Publishing in Materials, Advanced Polymer Nanocomposites, Woodhead Publishing, 2022, Pages 267-317, ISBN 9780128244920, https://doi.org/10.1016/B978-0-12-824492-0.00010-6.; Harpreet Singh, Kirandeep Kaur, Role of nanotechnology in research fields: Medical sciences, military & tribology- A review on recent advancements, grand challenges and perspectives, Materials Today: Proceedings, 2023, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2023.02.061. (https://www.sciencedirect.com/science/article/pii/S2214785323005783); Priyanshi Saini, Kamalesu, Lalita, Manikanika, Review on nanotechnology “Impact on the food services industry”, Materials Today: Proceedings, 2023, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2023.04.377.; Aloysius F. Hepp, Jerry D. Harris, Allen W. Apblett, Andrew R. Barron, Chapter 17 - Commercialization of single-source precursors: Applications, intellectual property, and technology transfer, Editor(s): Allen W. Apblett, Andrew R. Barron, Aloysius F. Hepp, Nanomaterials via Single-Source Precursors, Elsevier, 2022, Pages 563-600, ISBN 9780128203408, https://doi.org/10.1016/B978-0-12-820340-8.00008-3.; Arkadiy Larionov, Yulia Larionova, Ludmila Selivanova, Regional Peculiarities of Energy Saving Development During the Exploitation of Housing and Underground Housing and Utility Sector Objects, Procedia Engineering, Volume 165, 2016, Pages 1229-1232, ISSN 1877-7058, https://doi.org/10.1016/j.proeng.2016.11.844.; Mahendra L. Shelar, Vinod B. Suryawanshi, Experimental investigation and characterization of the tensile and flexural properties of amine functionalized graphene enhanced nanocomposite prepregs, Materials Today: Proceedings, 2023, ISSN 2214-7853, https://doi.org/10.1016/j.matpr.2023.06.371.; A. B. Shivshambhu Kumar, "Potential applications of nanomaterials in oil and gas well cementing: Current status, challenges and prospects," Journal of Petroleum Science and Engineering, vol. 213, pp. 1-18, 2022.; L. Ivanov, O. Borisova and S. R. Miminova, "The inventions in nanotechnologies as practical solutions. Part I.," Nanotekhnologii v Stroitel'stve, vol. 11, no. 1, pp. 91-101, 2019.; F. A. Shilar, S. V. Ganachari y V. B. Patil, “Advancement of nano-based construction materials-A review”, Construction and Building Materials, vol. 359, pp. 1-41, 2022; M. Luna, J.J. Delgado, T. Montini, L.M.L. Almoraima Gil, P. Fornasiero and M.J. Mosquera, "Photocatalytic TiO2 nanosheets-SiO2 coatings on concrete and limestone: An enhancement of de-polluting and self-cleaning properties by nanoparticle design," Construction and Building Materials, vol. 338, pp. 1-13, 2022.; Z. Wang, Q. Yu, P. Feng and H. Brouwers, "Variation of self-cleaning performance of nano-TiO2 modified mortar caused by carbonation: From hydrates to carbonates," Cement and Concrete Research, vol. 158, pp. 1-15, 2022.; A. A. Firoozi, M. Naji, M. Dithinde and A. A. Firoozi, "A Review: Influence of Potential Nanomaterials for Civil Engineering Projects," Iranian Journal of Science and Technology, Transactions of Civil Engineering, vol. 45, p. 2057–2068, 2020.; A. A. Alizadehmojarad, X. Zhou, A. G. Beyene, K. E., Chacon, Y. Sung, R. Pinals, L. Vuković, "Binding Affinity and Conformational Preferences Influence Kinetic Stability of Short Oligonucleotides on Carbon Nanotubes," Advanced Materials Interfaces, vol. 7, no. 15, p. 2000353, 2020.; J. Tang, X. Wang, J. Zhang, J. Wang, W. Yin, D.S. Li, and T. Wu, "A chalcogenide-cluster-based semiconducting nanotube array with oriented photoconductive behavior," Nature Communications, vol. 12, no. 1, p. 4275, 2021.; A. S. Dahlan, "Smart and Functional Materials Based Nanomaterials in Construction Styles in Nano-Architecture," Silicon, vol. 11, pp. 1949-1953, 2019.; A. Adesina, "Overview of Workability and Mechanical Performance of Cement-Based Composites Incorporating Nanomaterials," Silicon, vol. 14, pp. 135-144, 2020.; A. M. Onaizi, G. F. Huseien, N. H. A. S. Lim, M. Amran and M. Samadi, "Effect of nanomaterials inclusion on sustainability of cement-based concretes: A comprehensive review," Construction and Building Materials, vol. 306, pp. 1-20, 2021.; A. Z. Aljenbaz y Ç. Çağnan, “Evaluation of Nanomaterials for Building Production within the Context of Sustainability”, European Journal of Sustainable Development, vol. 9, pp. 53-65, 2020.; P. D. Bonilla Nieto, J. S. Carrillo Sanabria, y J. R. Camargo López, “Solar energy manager with PSOC5LP”, Vis. Electron., vol. 13, n.º 1, pp. 112–122, ene. 2019. https://doi.org/10.14483/22484728.14426; D. J. Arcila Perozo, L. Y. López López, y K. S. Novoa Roldán, ”Robotic system based on ant behavior for optimizing shortest path finding”, Vis. Electron., vol. 17, n.º 1, abr. 2023.; Yener, S. C., & Mutlu, R. (2018). A microcontroller-based ECG signal generator design utilizing microcontroller PWM output and experimental ECG data. 2018 Electric Electronics, Computer Science, Biomedical Engineering’s’ Meeting, EBBT 2018, 1-4. https://doi.org/10.1109/EBBT.2018.8391465; Rangayyan, R. M. (2002). BIOMEDICAL SIGNAL ANALYSIS A Case-Study Approach.; León, F., Rodríguez Lozano, F. J., Cubero Fernández, A., Palomares, J. M., & Olivares, J. (2019). SysGpr: Sistema de generación de señales sintéticas pseudo-realistas. Revista Iberoamericana De Automática, 16 (3), 369-379.; Anowarul Fattah, S. (2012). Identifying the Motor Neuron Disease in EMG Signal Using Time and Frequency Domain Features with Comparison. Signal & Image Processing: An International Journal, 3 (2), 99-114. https://doi.org/10.5121/sipij.2012.3207; De Luca, C. J. (1979). Physiology and Mathematics of Myoelectric Signals. IEEE Transactions on Biomedical Engineering, BME-26 (6), 313-325. https://doi.org/10.1109/TBME.1979.326534; Selvan, V. A. (2011). Single-fiber EMG: A review. Ann Indian Acad Neurol.; Wu, J., Li, X., Liu, W., & Jane Wang, Z. (2019). SEMG Signal Processing Methods: A Review. Journal of Physics: Conference Series, 1237 (3). https://doi.org/10.1088/1742- 6596/1237/ 3/032008; Widodo, A., Puspitaningayu, P., Anifah, L., & Firmansyah, R. (2018). An ArdiunoSimulink Based ECG Waveform Generator. 2018 2nd Borneo International Conference on Ap- plied Mathematics and Engineering, BICAME 2018, 338-342. https://doi.org/10.1109/ BICAME45512.2018.1570504879; DALCAME. (2005). Electromiografía. http ://www.dalcame.com/emg.html#.X4o6m9BKjIV (accessed: 16.10.2020).; López Chávez, H. I. (2020). Detección de la LRD en el ritmo cardiaco. APUNTES DE CLASE. Mahabalagiri, A. K., Ahmed, K., & Schlereth, F. (2011). A novel approach for simulation, measurement and representation of surface EMG (sEMG) signals. Conference Record - Asilomar Conference on Signals, Systems and Computers, 476- 480. https://doi.org/10.1109/ACSSC.2011.6190045; Ruiz Rubio, R. (1999). Aplicaciones de las señales electromiográficas. http://www.encuentros.uma.es/encuentros53/aplicaciones.%20html#:∼:%20text=Las% 5C%20se%5C%C3%5C%B1ales%5C%20EMG%5C%20tienen%5C%20una%5C%20f recuencia%5C%20que%5C%20oscila%5C%20entre%5C%2050,ser%5C%20menor% 5C%20de%5C%20300%5C%20Hz. (accessed: 16.10.2020).; Tabernig, C., Acevedo, R., & Fernández, J. (2007). INFLUENCIA DE LA FATIGA MUSCULAR EN LA SEÑAL ELECTROMIOGRÁFICA DE MÚSCULOS ESTIMULADOS ELÉCTRICAMENTE. Revista EIA, 111-119.; Alvarés Osorio, L. (2007). Acondicionamiento de señales bioeléctricas. https://www.coursehero.com/file/p3rjpjoo/2-Tipos-de-se%5C%C3%5C%B1alesbioel%5C%C3%5C%A9ctricas-6-nervous-system-a-trav%5C%C3%5C%A9s-demotor-end-plates/(accessed: 16.10.2020).; Mcgill, K. C., Lateva, Z. C., & Marateb, H. R. (2005). EMGLAB. http://emglab.net/emglab/index.php; Nikolic, M. (2001). Detailed Analysis of Clinical Electromyography Signals EMG Decomposition, Findings and Firing Pattern Analysis in Controls and Patients with Myopathy and Amy- trophic Lateral Sclerosis [Tesis doctoral, Faculty of Health Science, University of Copenhagen].; Téllez, M., Mejía, J., López, H., & Hernández, C. (2020). Random Number Generator with LongRange Dependence and Multifractal Behavior Based on Memristor. Electronics, 9 (10). https://doi.org/10.3390/electronics9101607; Initial J. Barrios., Tratamiento del sindrome del tunel carpiano. estudio de un caso clinico, Available online: https://mbfisioterapia.wordpress.com/tag/tunel-carpiano/, 2012, (accessed on 27-08-2023).; Diego A. B. V. and Ferro R. E, Estudio de modelos propuestos para el nervio mediano sano y con síndrome de túnel carpiano. Available online: https://revistas.udistrital.edu.co/index.php/NoriaIE/article/view/16353/15643 , 2019, (accessed on 28-08-2023).; L. L. A., Síndrome del túnel del carpo, Available online: https://www.medigraphic.com/pdfs/orthotips/ot-2014/ot141g.pdf , 2014, (accessed on 28-08-2023). Revista Orthotips.; R. D. G. F and D. F, Síndrome del túnel carpiano carpal tunnel syndrome,Revista Habanera de Ciencias Médicas, vol. 13, pp. 728–741, 2014. [Online]. Available: http://scielo.sld.cu; M. E. D. Alguacil, A. C. Millán, R. L. Sánchez, A. M. Sánchez, M. F. Arrondo, and I. C. Hernández, Revisión bibliográfica síndrome del túnel carpiano. intervención enfermera. Available online: https://revistasanitariadeinvestigacion.com/revision-bibliograficasindrome-del-tunel-carpiano-intervencion-enfermera/ , 2022, (accessed on 29-08- 2023).; J. O. G, Síndrome de túnel carpiano y accidente de tráfico. https://www.peritajemedicoforense.com/OJEDA.htm#:∼:text=El%20S%C3%ADndrome %20de%20T%C3%%20BAnel%20Carpiano,a%20traumatismo%20sobre%20la%20mu %C3%B1eca, 2001, (accessed on 29-08-2023).; M. B. Tejedor, J. A. Cervera, R. G. Lahiguera, and A. L. Ferreres, Análisis de factores de riesgo laborales y no laborales en síndrome de túnel carpiano (stc) mediante análisis bivariante y multivariante, https://scielo.isciii.es/scielo.php?script=sci arttext&pid=S1132-62552016000300004, 2016, (accessed on 01-09-2023). Valencia. Revista Scielo.; A. M. R., Síndrome del túnel carpiano. revisión no sistemática de la literatura. https://revistas.unisanitas.edu.co/index.php/rms/article/view/436, 2019, (accessed on 01-09-2023). Revista Médica Sanitas.; G. C. G. P., A. F. G. E., and E. A. G. A., Síndrome del túnel del carpo. Revista morfología. https://revistas.unal.edu.co/index.php/morfolia/article/view/10857#:∼:text=El%20S%C 3%ADndrome%20del%20T%C3%BAnel%20de,causas%20locales,%20regionale s%20y%20sist%C3%A9micas., 2009, (accessed on 02-09-2023). Universidad Nacional de Colombia.; Y. A. M. M., L. V. C. S., and M. A. T. S., Prevalencia de signos y síntomas de síndrome del túnel carpiano y sus factores asociados, en empleados administrativos de la universidad santo tomás sede floridablanca, durante el semestre del 2016. https://repository.usta.edu.co/bitstream/handle/11634/10218/YohannaMirandaLizethcala-%202017.pdf?sequence=1&isAllowed=y, 2017, (accessed on 23-09-2023). Universidad Santo Tomás.; U. M. Vázquez, I. D. C. Carrera, A. Alonso-Calvete, and Y. González-González, Eficacia del kinesiotape en el síndrome del túnel carpiano. una revisión sistemática, https://scielo.isciii.es/scielo.php?pid=S1132- 62552022000100011&script=sciarttext&tlng=pt, 2022, accedido 6-09-2023.; E. Cabrera, “El coeficiente de correlacion de los rangos de spearman caracterizacion,”http://scielo.sld.cu/pdf/rhcm/v8n2/rhcm17209.pdf, 2009, accedido 8- 09-2023.; IBM, “Estadísticos de tablas cruzadas,” https://www.ibm.com/docs/es/spss-statistics/ saas?topic=crosstabs-statistics, 2021, accedido 8-09-2023.; H. L. J. Diego, E. C. Franklin, R. J. E, C. R. J. Gerardo, T. S. C. Andrés, A. T. M. Karina, C. S. S. Milena, and B. P. V. José, “Sobre el uso adecuado del coeficiente de correlación de pearson: definición, propiedades y suposiciones,” https://www.redalyc.org/journal/559/55963207025/55963207025.pdf, 2018, accedido 8- 09-2023.; S. I. M. Orlando, “Coeficiente de correlación; coeficiente de correlación de spearman; estadística; coeficiente de correlación por rangos,” http://repositorio.utn.edu.ec/handle/123456789/768, 2011, accedido 15-09-2023.; B. M.H., A. G. O.P, L. Serrato, and J. A. Garnica, “Correlación no-paramétrica y su aplicación en la investigaciones científica non-parametric correlation and its application in scientific research,” http://www.spentamexico.org/v9-n2/A5.9(2)31-40.pdf, 2014, accedido 15-09-2023.; NCAN National Center for Adaptative Neurotechnologies, Documentation 2nd Wadsworth BCI Dataset (P300 Evoked Potentials) Data Acquired Using BCI2000 P3 Speller Paradigm, 1, 2002.; M.S.S.T.N.H Yağan-Mussellim-Arslan-Çakar-Alp-Ozkan, "A new benchmark dataset for P300 ERP-based BCI applications", Digital Signal Processing, vol. 135, pp. 1-11, April 2023.https://doi.org/10.1016/j.dsp.2023.103950.; L. E. A. G. P. Korczowski-Ostaschenko-Andreev-Cattan-Coelho Rodrigues, et al. Brain Invaders calibration-less P300-based BCI using dry EEG electrodes Dataset, (bi2014a). [Research Report] GIPSA-lab. 2019. ffhal-02171575f; A. M. E. D. D. C. R. M. T. L. M. Gramfort-Luessi-Larson-Engemann-StrohmeierBrodbeck-Goj-Jas-Brooks-Parkkonen-Hämäläinen. MEG and EEG data analysis with MNE-Python. Frontiers in Neuroscience, 7(267):1–13, 2013. doi:10.3389/fnins.2013.00267.; Haghighatpanah, N., Amirfattahi, R., Abootalebi, V., & Nazari, B. (2012). A two stage single trial P300 detection algorithm based on independent component analysis and wavelet transforms. 2012 19th Iranian Conference of Biomedical Engineering (ICBME), 324-329.; Neda Haghighatpanah, Rasoul Amirfattahi, Vahid Abootalebi, and Behzad Nazari. A single channel-single trial p300 detection algorithm. In 2013 21st Iranian Conference on Electrical Engineering (ICEE), pages 1–5, 2013; S. K. Haider, A. Jiang, M. A. Jamshed, H. Pervaiz and S. Mumtaz, "Performance Enhancement in P300 ERP Single Trial by Machine Learning Adaptive Denoising Mechanism," in IEEE Networking Letters, vol. 1, no. 1, pp. 26-29, March 2019, doi:10.1109/LNET.2018.2883859.; Praveen Kumar Shukla, Rahul Kumar Chaurasiya, and Shrish Verma. Performance improvement of p300-based home appliances control classification using convolution neural network. Biomedical Signal Processing and Control, 63, 1 2021.; Samima, S., Sarma, M., Samanta, D. et al. Estimation and quantification of vigilance using ERPs and eye blink rate with a fuzzy model-based approach. Cogn Tech Work 21, 517–533 (2019). https://doi.org/10.1007/s10111-018-0533-8; A. Boudjella, M. Y. Boudjella and B. Bachir, "Epileptic Disease Prediction Using Graphic User Interface–Machine Learning Algorithm," 2022 7th International Conference on Image and Signal Processing and their Applications (ISPA), Mostaganem, Algeria, 2022, pp. 1-8, doi:10.1109/ISPA54004.2022.9786366.; Heras, J. M. (2019, noviembre 17). Precision, Recall, F1, Accuracy en clasificación. [Online] Iartificial.net. Available at https://www.iartificial.net/precision-recall-f1- accuracy-en-clasificacion/; C. F. Blanco-D ́ıaz, C. D. Guerrero-Méndez, and A. F. Ruiz-Olaya. Enhancing p300 detection using a band-selective filter bank for a visual p300 speller. IRBM, 44, 6 2023; E Solis-Escalante, G Gabriel Gentiletti, and O Yanez-Suarez. Single trial p300 detection based on the empirical mode decomposition. In 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pages 1157– 1160, 2006.; C. F. Blanco-D ́ıaz, C. D. Guerrero-M ́endez, and A. F. Ruiz-Olaya. Enhancing p300 detection using a band-selective filter bank for a visual p300 speller. IRBM, 44, 6 2023; R. A. Neira- Ricouz, " Fotografia Aerea", Tesis Ing, Universidad Austral de Chile, Valdivia, Chile, 2005.; D. I. Gómez, R. Castrillón, " Reconocimiento Automático De Ganado Bovino A Partir De Imágenes Aéreas Tomadas Con Drones: Un enfoque exploratorio", III Congreso Internacional en Inteligencia Ambiental, Ingeniería de Software y Salud Electrónica y Móvil, 32-39, Pereira Colombia, 2019.; Airdroneview, 4 julio 2014, “Historia de la fotografía aérea”[Blog], [Online]. Recuperado de: https://airdroneview.com/2014/07/04/historia-de-la-fotografia-aerea/ .; F. Fernández García, " Fotografía aérea histórica e historia de la fotografía aérea en España”, Revista ERIA, Departamento de Geografía. Universidad de Oviedo, España, pp . 217-240, 2015.; M. Blanco Pérez. (2021). Fotografía aérea con tecnología drone. Tipología y aplicaciones. Discursos Fotograficos, 16(29), pp.76–101. https://doi.org/10.5433/1984-7939.2020v16n29p76; FJT Historia, medicina y otras artes, marzo 2016, “Las primeras fotografías aéreas de la Historia”[Blog],[Online]. Recuperado de: https://franciscojaviertostado.com/2016/03/14/las-primeras-fotografias-aereas-de-lahistoria/.; A Berrondo UrruzolaD. I, "Detección de carreteras en imágenes de reconocimiento remoto mediante deep", Grado en Ingeniería Informática Computación, Univeridad del pais vasco, Facultad de informatica, 2020.; A. Yasin Yiğit, A. Kocatepe, " Automatic road detection from orthophoto images", mersin photogrametri journal, 2(1); 10-17, e ISSN 2687-654X, 2020 .; Chaki, N., Shaikh, S.H., Saeed, K. (2014). A Comprehensive Survey on Image Binarization Techniques. In: Exploring Image Binarization Techniques. Studies in Computational Intelligence, vol 560. Springer, New Delhi. https://doi.org/10.1007/978- 81-322-1907-1_2; RAE, diccionario real academia de la lengua española, actualización 2022, “consulta del termino correlación”[Online]. Recuperado de: https://dle.rae.es/correlaci%C3%B3n?m=form; Máxima formación, julio 2020, “¿Qué Es La Correlación Estadística Y Cómo Interpretarla?”, [Blog], [Online]. Recuperado de: https://dle.rae.es/correlaci%C3%B3n?m=form; P. Sinha, B. Horgan, R. Ewing, E. Rampe, M. Lapotre, M. Nachon, M. Thorpe, A. Rudolph, C. Bedford, K. Maso2, E. Champion, P. Gray, E. Reid, M. Faragalli, “Decorrelation stretches(dcs) of visible images as a tool for sedimentary provenance investigationson earth and mars”, NTRS - NASA Technical Reports Server, March 16, 2020; Farrand, W. H., J. F. Bell III, J. R. Johnson, M. S. Rice, B. L. Jolliff, and R. E. Arvidson (2014), “Observations of rock spectral classes by the Opportunity rover’s Pancam on northern Cape York and on Matijevic Hill, Endeavour Crater, Mars”, J. Geophys. Res. Planets, 119, 2349–2369, doi:10.1002/2014JE00464.; M. Peikari, A. L. Martel, "Automatic cell detection and segmentation from H and E stained pathology slides using colorspace decorrelation stretching", Proc. SPIE 9791, Medical Imaging 2016: Digital Pathology, 979114 (23 March 2016); https://doi.org/10.1117/12.2216507; D. Hema1, S. Kannan. “Interactive Color Image Segmentation using HSV Color Space”, Science and Technology Journal, Vol. 7 Issue: 1 ISSN: 2321-3388, 2020; The MathWorks Inc,“Image Processing Toolbox For Use with MATLAB®”, decorstretch function, Version 3, User's Guide, https://www.mathworks.com/help/images/ref/decorrstretch.html.; T. Gevers, J. Weijer, H Stokman, “Color Image Processing: Chapter Color Feature Detection”. Social Science Computing Review, 1 st ed. England. edit. CRC Press, pp. 22, 2006. eBook ISBN9781315221526.; The MathWorks Inc,“Image Processing Toolbox For Use with MATLAB®”, imfill function, Version 3, User's Guide, https://la.mathworks.com/help/images/ref/imfill.html?searchHighlight=imfill&s_tid=srch title_support_results_1_imfill.; The MathWorks Inc,“Image Processing Toolbox For Use with MATLAB®”, bwareadopen function, Version 3, User's Guide. https://la.mathworks.com/help/images/ref/bwareaopen.html?searchHighlight=bwareao pen&s_tid=srchtitle_support_results_1_bwareaopen; Shutterstock,” Imágenes libres de regalías de Maldivas”, [Online]. Recuperado de: https://www.shutterstock.com/es/search/maldivas; National Geographic, “Vista aérea del complejo arqueoastronómico de Chankillo, en Perú”. Foto: Ministerio de Cultura de Perú, [Online]. Recuperado de: https://historia.nationalgeographic.com.es/a/chankillo-observatorio-solar-mas-antiguoamerica_19020; M. Franzese and A. Iuliano, “Hidden Markov models,” in Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Elsevier, 2018, pp. 753–762. Doi:10.1016/B978-0-12-809633-8.20488-3.; B.-J. Yoon, “Hidden Markov Models and their Applications in Biological Sequence Analysis,” Cur Genomics, vol. 10, no. 6, pp. 402–415, Sep. 2009, Doi:10.2174/138920209789177575.; P. C. Chang, J. J. Lin, J. C. Hsieh, and J. Weng, “Myocardial infarction classification with multilead ECG using hidden Markov models and Gaussian mixture models,” Applied Soft Computing Journal, vol. 12, no. 10, pp. 3165–3175, Oct. 2012, Doi:10.1016/j.asoc.2012.06.004.; T. Navarrete, “Detección de anomalías en la carga de un procesador utilizando modelos ocultos de Markov.,” Tesis de maestría, Instituto tecnológico de Morelia, Morelia, Michoacán, pp. 1, 2007. Accessed: Sep. 11, 2023. [Online]. Available: http://www.asiat.com.mx/tomas/tesismaestria/micrositio/node2.html; Ö. Yavuz, M. Calp, and H. Erkengel, “Prediction of breast cancer using machine learning algorithms on different datasets,” Ingenieria Solidaria, vol. 19, no. 1, pp. 1–32, Jun. 2023, doi:10.16925/2357-6014.2023.01.08.; DANE, “Estadísticas vitales (EEVV),” pp. 1, 2023. Accessed: Sep. 11, 2023. [Online]. Available: https://www.dane.gov.co/files/investigaciones/poblacion/pre_estadisticasvitales_IIItrim_2022p r.pdf; W. Gersch, P. Lilly, and E. Dong, “PVC Detection by the Heart-Beat Interval Data-Markov Chain Approach,” COMPUTERS AND BIOMEDICAL RESEARCH, vol. 8, pp. 370–378, 1975, Doi: https://doi.org/10.1016/0010-4809(75)90013-0.; A. H. Kadish et al., “ACC/AHA clinical competence statement on electrocardiography and ambulatory electrocardiography. A report of the ACC/AHA/ACP-ASIM Task Force on Clinical Competence (ACC/AHA Committee to Develop a Clinical Competence Statement on Electrocardiography and Ambulatory Electrocardiography),” J Am Coll Cardio, vol. 38, no. 7, pp. 2091–2100, 2001, Doi:10.1016/s0735-1097(01)01680-1.; R. V. Andreão, B. Dorizzi, and J. Boudy, “ECG signal analysis through hidden Markov models,” IEEE Trans Biomed Eng, vol. 53, no. 8, pp. 1541–1549, Aug. 2006, doi:10.1109/TBME.2006.877103.; M. H. Crawford et al., “ACC/AHA guidelines for ambulatory electrocardiography: Executive summary and recommendations: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Revise the Guidelines for Ambulatory Electrocardiography): Developed in Collaboration with the North American Society for Pacing and Electrophysiology,” Circulation, vol. 100, no. 8. Lippincott Williams and Wilkins, pp. 886–893, Aug. 24, 1999. Doi:10.1161/01.CIR.100.8.886.; Sayed Khaled, A. Khalaf, and Y. Kadah, “Arrhythmia classification based on novel distance series transform of phase space trajectories,” Annu Int Conf IEEE Eng Med Biol Soc, pp. 5195– 8, 2015, Doi:10.1109/EMBC.2015.7319562.; M. Alvarez and R. Henao, “Combinacion de ppca y hmm para la identificación de infarto agudo de miocardio,” Scientia Et Technica, vol. 3, no. 32, pp. 139–144, 2006, doi: https://doi.org/10.22517/23447214.6253.; P. Laguna, A. Mark, A. Goldberg, and B. Moody, “A Database for Evaluation of Algorithms for Measurement of QT and Other Waveform Intervals in the ECG,” Compute Cardiol, pp. 673–76, 1997, Doi:10.1109/CIC.1997.648140.; A. L. Goldberger et al., “Physio Bank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.,” Circulation, vol. 101, no. 23, pp. 1–6, 2000, Doi:10.1161/01.cir.101.23.e215.; G. Moody and R. Mark, “The impact of the MIT-BIH Arrhythmia Database,” IEEE Engineering in Medicine and Biology Magazine, vol. 20, no. 3, pp. 45–50, 2001, Doi:10.1109/51.932724.; A. Taddei et al., “The European ST-T database: standard for evaluating systems for the analysis of ST-T changes in ambulatory electrocardiography,” Eur Heart J, vol. 13, no. 9, pp. 1164– 1172, 1992, Doi:10.1093/oxfordjournals.eurheartj.a060332.; R. Bousseljot, D. Kreiseler, and A. Schnabel, “Nutzung der EKG-Signaldatenbank CARDIODAT der PTB über das Internet,” Biomedizinische Technik, vol. 40, pp. 317–318, 1995, Doi: https://doi.org/10.1515/bmte.1995.40.s1.317.; F. Nolle, J. Badura, R. Catlett, H. Bowser, and M. Sketch, “CREI-GARD, a new concept in computerized arrhythmia monitoring systems,” Computers in Cardiology , pp. 515–518, 1987.; W. T. Cheng and K. L. Chan, “Classification of electrocardiogram using hidden Markov models,” Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. , vol. 20, no. 1, pp. 143–46, 1998, Doi:10.1109/IEMBS.1998.745850.; D. V. Filho and A. M. Cavalcanti, “MODELO PARA ANÁLISE DE ARRITMIAS CARDÍACAS USANDO CADEIAS DE MARKOV,” Proceedings of the XII SIBGRAPI , pp. 101–104, 1999, Accessed: Sep. 11, 2023. [Online]. Available: http://www.din.uem.br/sbpo/sbpo2005/pdf/arq0174.pdf; V. Kalidas and L. S. Tamil, “Detection of atrial fibrillation using discrete-state Markov models and Random Forests,” Compute Biol Med, vol. 113, pp. 1–14, Oct. 2019, Doi:10.1016/j.compbiomed.2019.103386.; P. Cheng and X. Dong, “Life-threatening ventricular arrhythmia detection with personalized features,” IEEE Access, vol. 5, pp. 14195–14203, Jul. 2017, Doi:10.1109/ACCESS.2017.2723258.; F. Nilsson, M. Stridh, and L. Sörnmo, “Frequency Tracking of Atrial Fibrillation using Hidden Markov Models,” Conf Proc IEEE Eng Med Biol Soc., pp. 1406–9, 2006, Doi:10.1109/IEMBS.2006.259677.; J. Oliveira, C. Sousa, and M. Coimbra, “Coupled hidden Markov model for automatic ECG and PCG segmentation,” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, pp. 1023–27, 2017, Doi:10.1109/ICASSP.2017.7952311.; S. Petrutiu, A. V. Sahakian, and S. Swiryn, “Abrupt changes in fibrillatory wave characteristics at the termination of paroxysmal atrial fibrillation in humans,” Europace, vol. 9, no. 7, pp. 466– 470, Jul. 2007, Doi:10.1093/europace/eum096.; M. A F Pimentel, M. D. Santos, D. B. Springer, and G. D. Clifford, “Heart beat detection in multimodal physiological data using a hidden semi-Markov model and signal quality indices,” Physio Meas, vol. 36, no. 8, pp. 1717–1727, Aug. 2015, Doi:10.1088/0967-3334/36/8/1717.; A. K. Sangaiah, M. Arumugam, and G. Bin Bian, “An intelligent learning approach for improving ECG signal classification and arrhythmia analysis,” Artif Intell Med, vol. 103, pp. 1–14, Mar. 2020, Doi:10.1016/j.artmed.2019.101788.; H. Kwok, J. Coult, J. Blackwood, N. Sotoodehnia, P. Kudenchuk, and T. Rea, “A method for continuous rhythm classification and early detection of ventricular fibrillation during CPR,” Resuscitation, pp. 90–97, 2022, Doi:10.1016/j.resuscitation.2022.05.019.; L. A. Levin et al., “A cost-effectiveness analysis of screening for silent atrial fibrillation after ischaemic stroke,” Europace, vol. 17, no. 2, pp. 207–214, Dec. 2014, Doi:10.1093/europace/euu213.; G. H. Tison, J. Zhang, F. N. Delling, and R. C. Deo, “Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery,” Circ Cardiovasc Qual Outcomes, vol. 12, no. 9, pp. 1–12, Sep. 2019, Doi:10.1161/CIRCOUTCOMES.118.005289.; W. H. Tang, W. H. Ho, and Y. J. Chen, “Retrieving hidden atrial repolarization waves from standard surface ECGs,” Biomed Eng Online, vol. 17, pp. 1–11, Nov. 2018, Doi:10.1186/s12938-018-0576-3.; M. Altuve, G. Carrault, A. Beuchée, P. Pladys, and A. I. Hernández, “Online apnea–bradycardia detection based on hidden semi-Markov models,” Med Biol Eng Compute, vol. 53, no. 1, pp. 1– 13, Jan. 2015, Doi:10.1007/s11517-014-1207-1.; S. Masoudi and et al., “Early detection of apnea-bradycardia episodes in preterm infants based on coupled hidden Markov model,” IEEE International Symposium on Signal Processing and Information Technology, Athens, Greece, pp. 243–48, 2013, Doi:10.1109/ISSPIT.2013.6781887.; N. Montazeri Ghahjaverestan, M. B. Shamsollahi, D. Ge, A. Beuchée, and A. I. Hernández, “Apnea bradycardia detection based on new coupled hidden semi Markov model,” Med Biol Eng Comput, pp. 1–11, 2020, Doi:10.1007/s11517-020-02277-8.; A. Sadoughi, M. B. Shamsollahi, E. Fatemizadeh, A. Beuchée, A. I. Hernández, and N. Montazeri Ghahjaverestan, “Detection of Apnea Bradycardia from ECG Signals of Preterm Infants Using Layered Hidden Markov Model,” Ann Biomed Eng, vol. 49, no. 9, pp. 2159–2169, Sep. 2021, Doi:10.1007/s10439-021-02732-z.; E. D. Übeyli, “Combining recurrent neural networks with eigenvector methods for classification of ECG beats,” Digital Signal Processing: A Review Journal, vol. 19, no. 2, pp. 320–329, 2009, Doi:10.1016/j.dsp.2008.09.002.; C. Zhang, G. Wang, J. Zhao, P. Gao, J. Lin, and H. Yang, “Patient-specific ECG classification based on recurrent neural networks and clustering technique,” 2017 13th IASTED International Conference on Biomedical Engineering (BioMed), Innsbruck, Austria, pp. 63–67, 2017, Doi:10.2316/P.2017.852-029.; Z. Xiong, M. K. Stiles, and J. Zhao, “Robust ECG signal classification for detection of atrial fibrillation using a novel neural network,” in Computing in Cardiology, IEEE Computer Society, 2017, pp. 1–4. Doi:10.22489/CinC.2017.066-138; M. Liam and F. Precioso, “Atrial fibrillation detection and ECG classification based on convolutional recurrent neural network,” in Computing in Cardiology, IEEE Computer Society, 2017, pp. 1–4. Doi:10.22489/CinC.2017.171-325.; Y. C. Chang, S. H. Wu, L. M. Tseng, H. L. Chao, and C. H. Ko, “AF Detection by Exploiting the Spectral and Temporal Characteristics of ECG Signals with the LSTM Model,” in Computing in Cardiology, IEEE Computer Society, Sep. 2018, pp. 1–4. Doi:10.22489/CinC.2018.266.; H. W. Lui and K. L. Chow, “Multiclass classification of myocardial infarction with convolutional and recurrent neural networks for portable ECG devices,” Inform Med Unlocked, vol. 13, pp. 26–33, Jan. 2018, Doi:10.1016/j.imu.2018.08.002.; G. D. Clifford et al., “AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017,” in Computing in Cardiology, IEEE Computer Society, 2017, pp. 1–4. Doi:10.22489/CinC.2017.065-469.; S. Singh, S. K. Pandey, U. Pawar, and R. R. Janghel, “Classification of ECG Arrhythmia using Recurrent Neural Networks,” Procedia Compute Sci, vol. 132, pp. 1290–1297, 2018, Doi:10.1016/j.procs.2018.05.045.; Li X, Qi X, Chen Z, Hou Y, Yang Y, and Liang Q, “Affective Stress Rating Method Based on Improved Hidden Markov Model,” Chinese, vol. 33, no. 3, pp. 533–538, 2016.; C. Ying, Z. Xin, and C. Wenxi, “Automatic sleep staging based on ECG signals using hidden Markov models,” Annu Int Conf IEEE Eng Med Biol Soc ., pp. 530–3, 2015, Doi:10.1109/EMBC.2015.7318416.; F. Sandberg, M. Stridh, and L. Sörnmo, “Frequency tracking of atrial fibrillation using hidden Markov models,” IEEE Trans Biomed Eng, vol. 55, no. 2, pp. 502–511, Feb. 2008, Doi:10.1109/TBME.2007.905488.; L. Rincón, “Introducción a los procesos estocásticos,” UNAM, México, pp. 120-180, 2011. [Online]. Available: http://www.matematicas.unam.mx/lars; A. Alaa, S. Hu, and M. Schaar, “Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis,” International Conference on Machine Learning , pp. 60–69, 2017, Doi: https://doi.org/10.48550/arXiv.1705.05267.; J. Bilmes, “A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models,” International computer science institute, vol. 4, no. 510, p. 126, 1998, Accessed: Sep. 11, 2023. [Online]. Available: https://f.hubspotusercontent40.net/hubfs/8111846/Unicon_October2020/pdf/bilmes-emalgorithm.pdf; L. R. Rabiner, “A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition,” Proceedings of the IEEE, vol. 77, no. 2, pp. 257–286, 1989, Doi:10.1109/5.18626.; A. Cohen, “Hidden Markov models in biomedical signal processing,” Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Biomedical Engineering Towards the Year 2000 and Beyond, vol. 3, pp. 1145–50, 1998, Doi:10.1109/IEMBS.1998.747073; Al-Hamadi, H., Gawanmeh, A., & Al-Qutayri, M. (2016). An automatic ECG generator for testing and evaluating ECG sensor algorithms. Proceeding of 2015 10th International Design and Test Symposium, IDT 2015, 78-83. https://doi.org/10.1109/IDT.2015.7396740; Yener, S. C., & Mutlu, R. (2018). A microcontroller-based ECG signal generator design utilizing microcontroller PWM output and experimental ECG data. 2018 ElectricElectronics, Computer Science, Biomedical Engineering’s’ Meeting, EBBT 2018, 1-4. https://doi.org/10.1109/EBBT.2018.8391465; Bear, M., Connors, B., & Paradiso, M. (2016). Neuroscience: Exploring the Brain. Wolters Kluwer. https://books.google.com.co/books?id=vVz4oAEACAAJ; López Chávez, H. I. (2020). Detección de la LRD en el ritmo cardiaco. APUNTES DE CLASE.; Park, K., & Willinger, W. (2000). Self-Similar Network Traffic and Performance Evaluation (1st). John Wiley & Sons, Inc.; Orozco, S. L., Cerda Villafaña, G., Cervantes, G. A., & Cisneros, M. T. (2010). Analysis of LRD Series with Time-Varying Hurst Parameter Análisis de Series LRD con Parámetro de Hurst Variante en el Tiempo. 13 (3), 295-312. http://www.fimee.ugto.mx/profesores/sledesma/documentos/; Ceballos, R. F., & Largo, F. F. (2018). On The Estimation of the Hurst Exponent Using Adjusted Rescaled Range Analysis, Detrended Fluctuation Analysis and Variance Time Plot: A Case of Exponential Distribution; Pujolle, G., Perros, H., Fdida, S., Korner, U., & Stavrakakis, I. (2000). Networking 2000 Broad- band Communications, High Performance Networking, and Performance of Communication Networks: IFIP-TC6/European Commission International Conference Paris, France, May 14–19, 2000 Proceedings. https://doi.org/10.1007/3-540-45551-5; Sheluhin, O., Smolskiy, S., & Osin, A. (2007). Self-Similar Processes in Telecommunications. John Wiley &; Sons, Inc.; Simonsen, I., Hansen, A., & Nes, O. M. (1998). Determination of the Hurst exponent by use of wavelet transforms. Physical Review E - Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 58 (3), 2779-2787. https://doi.org/10.1103/PhysRevE.58.2779; R. A. Robayo Salazar, P. E. Mattey Centeno, Y. F. Silva Urrego, D. M. Burgos Galindo y S. Delvasto Arjona, «Los residuos de la construcción y demolición en la ciudad de Cali: un análisis hacia su gestión, manejo y aprovechamiento,» Tecnura, vol. 19, nº 44, pp. 157-170, 2015.; Observatorio Ambiental de Bogotá, «Observatorio Ambiental de Bogotá,» 30 Julio 2023. [En línea]. Available: https://oab.ambientebogota.gov.co/residuos-de-construccion-ydemolicion/. [Último acceso: septiembre 2023].; Invías, «Normas y especificaciones 2012 invías,» 2012. [En línea]. Available: https://www.umv.gov.co/sisgestion2019/Documentos/APOYO/GLAB/GLAB-DE003_V1_Normas_Invias_Seccion_400-13.pdf. [Último acceso: septiembre 2023].; Normas técnicas Colombianas, «Concretos, especificaciones de los agragados para concreto NTC 174,» p. 5, 2000. [En línea]. Available: https://www.emcali.com.co/documents/148832/183512/NTC+174+de+2000.pdf/. [Último acceso: Septiembre 2023].; J. L. Rojas Ramírez y J. E. Berrío Mutiz, «Elaboración de concreto a partir de material de escombros de concreto,» Quindío - Colombia, 2019.; B. E. García Velásquez y L. M. Díaz Morales, «Proyecto de investigación evaluación de la resistencia a la compresión del concreto utilizando el cuesco proveniente de los residuos de fruto fresco de la palma africana y el concreto de residuos de construcción y demolición en obras civiles (rcd),» Villavicencio, 2019.; S. Peña Muñoz, J. F. Terán Puerta, J. A. Molina Sánchez, H. D. Cañola, A. BuilesJaramillo y . J. Ubany Zuluaga, «Evaluación de las propiedades de residuos de construcción y demolición de concreto,» Cuaderno, vol. 10, nº 1, pp. 79-90, 2018.; L. Perez Hernández, J. Gomez Chimento, A. Contreras Bravo y Padilla RuizLiseth, «Resistencia a la compresión del concreto,» Researchgate, Octubre 2018.; L. León Consuegra y M. Hernández Puentes, «Comparación de los valores de resistencia a compresión del hormigón a la edad de 7 y 28 días.,» Revista de Arquitectura e Ingeniería, vol. 10, nº 1, pp. 1-9, 2016.; À. Alegre Arias, «Hormigones en masa con áridos reciclados procedentes de rcd para su uso en la fabricación de bloques de defensa portuarios.,» Barcelona, 2012.; G. Bossini, M. G. Nuñez Cáceres y H. D. Anaya, «Influencia de agregados reciclados provenientes de (RCD) en hormigón,» de IX Jornadas de ciencias y tecnologías de facultades de ingeniería del NOA, Santiago del Estero, 2018.; C. J. Zega, «Hormigones reciclados: caracterización de los agregados gruesos reciclados,» (Tesis de maestría), p. 28, 2008.; E. Pavón, M. Etxeberria y I. Martínez, «Propiedades del hormigón de árido reciclado fabricado con adiciones, activa e inerte,» Revista de la construcción, vol. 10, nº 3, pp. 4- 15, 2011.; S. P. Muñoz Perez, D. M. Diaz Sanchez, E. E. Gamarra Capuñay y J. A. Chaname Bustamante , «La influencoa de los RCD en reemplazo de los agregados para la elaboración del concreto: una revisión literaria,» Ecuadorian Science Journal, vol. 5, nº 2, pp. 107-120, 2021.; C. A. Pacheco Bustos, L. G. Fuentes Pumarejo, É. H. Sánchez Cotte y H. A. Rondón Quintana, «Residuos de construcción y demolición (RCD), una perspectiva de aprovechamiento para la ciudad de barranquilla desde su modelo de gestión,» Ingeniería y Desarrollo, vol. 35, nº 2, pp. 533-555, 2017.; IEEE, IEEE Standard for Information technology—Telecommunications and information exchange between systems Local and metropolitan area networks—Specific requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, vol. 2020. 2016. [Online]. Available: http://www.ieee.org/web/aboutus/whatis/policies/p9- 26.html.%0Ahttps://standards.ieee.org/standard/802_11ax-2021.html; “El nuevo 802.11ah conoce todo sobre Wi-Fi HaLow" :: Tecnocompras.” https://tecnocompras6.webnode.com.co/news/el-nuevo-802-11ah-conoce-todo-sobrewi-fi-halow/ (accessed Mar. 23, 2023).; Guías de Laboratorio para el estudio de señales Wi-Fi con el Equipo ANRITSU MS2830A de la Universidad Distrital Francisco José de Caldas, Manuel Fernando Cañas Soto, Brayan Alexander Estupiñan Avellaneda, José David Cely Callejas UDFJC 2023; M. Viseras, “Diseño De Una Guia De Prácticas De Laboratorio De Acuerdo Con Las Orientaciones Del Eees,” Enseñanza las Ciencias, Número Extra VIII Congr. Int. sobre Investig. en Didáctica las Ciencias, no. 1, pp. 1228–1233, 2009, [Online]. Available: https://pt.scribd.com/document/320878666/DISENO-DE-UNA-GUIA-DEPRACTICAS-DE-LABORATORIO-DE-ACUERDO-CON-LAS-ORIENTACIONESDEL-EEES; A. Alilla, A. Di Carlofelice, M. Faccio, I. Lucresi, and P. Tognolatti, “Software-defined satellite ranging measurements using laboratory signal analyzer,” 2014 IEEE Int. Work. Metrol. Aerospace, Metroaerosp. 2014 - Proc., pp. 332–336, 2014, doi:10.1109/METROAEROSPACE.2014.6865944.; P. Brochure, “Signal Analyzer,” SpringerReference, 2011, doi:10.1007/springerreference_24743.; A. Torres, “Ubiquiti airFiber – ¿Qué es BER (tasa de error de bit) en los radios airFiber? %7C Base de Conocimiento,” Ubiquiti. https://soporte.syscom.mx/es/articles/1439450- ubiquiti-airfiber-que-es-ber-tasa-de-error-de-bit-en-los-radios-airfiber (accessed Jul. 19, 2022).; O. Hernandez Cruz, “Diagrama de constelacion y modulaciones digitales avanzadas - Omar Hernández Cruz 17110937 Diagrama - StuDocu,” Universidad TecMilenio, 2021. https://www.studocu.com/es-mx/document/universidad-tecmilenio/ingenieria-decontrol/diagrama-de-constelacion-y-modulaciones-digitales-avanzadas/12619514 (accessed Jul. 19, 2022).; “Diagrama de constelación %7C PROMAX,” PROMAX, 2017. https://www.promax.es/esp/noticias/516/diagrama-de-constelacion/ (accessed Jul. 19, 2022).; Tektronix, “What Are Vector Network Analyzers %7C VNAs Explained %7C Tektronix.” https://www.tek.com/en/documents/primer/what-vector-network-analyzer-and-howdoes-it-work (accessed Jul. 19, 2022).; Tektronix, “Signal Generator %7C Tektronix.” https://www.tek.com/en/products/signalgenerators (accessed Jul. 19, 2022).; “Modelo pedagógico de la Facultad de Comunicaciones de la Universidad de Antioquia,” Feb. 2016. https://www.udea.edu.co/wps/wcm/connect/udea/fcc26266- 11ae-42c5-87abd8025d2bec9/MODELO+PEDAGÓGICO.pdf?MOD=AJPERES&CVID=lsLGwgF (accessed Aug. 05, 2022).; D. Noreña, “EL CONCEPTO DE PEDAGOGÍA EN LA OBRA PEDAGÓGICA DE RAFAEL FLÓREZ OCHOA ,” Univ. ANTIOQUIA Fac. Educ. Dep. Educ. Av. Maest. EN Educ. ÉNFASIS EN Form. Maest. , 2007, Accessed: Aug. 05, 2022. [Online]. Available: http://ayura.udea.edu.co:8080/jspui/bitstream/123456789/624/1/AA0384.pdf; M. Rosales, “Proceso evaluativo: evaluación sumativa, evaluación formativa y Assesment su impacto en la educación actual”; L. A. N. M. A. N. Committee, IEEE Std 802.11-2007: IEEE Standard for Information Technology-Telecommunications and Information Exchange between Systems-Local and Metropolitan Area Networks-Specific Requirements Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY, vol. 2020. 2007. [Online]. Available: http://scholar.google.com/scholar?q=related:K_aQPLd0dskJ:scholar.google.com/&hl= en&num=30&as_sdt=0,5%5Cnpapers3://publication/uuid/E731D645-DF33-45B5- 8882-A665213EA9D8; Anritsu MU181020A PPG 12.5Gb/s, “Anritsu corporation,” Analyzer, vol. 2, [Online]. Available: http://downloadfile.anritsu.com/Files/en-AU/Manuals/OperationManual/mu181020a_b_opm_e_17_0.pdf?f4739ea0f83b43ad1015d3937dbcf8be3aec 8f5de0897d0d745727bbd0217d9fa6b870ff705096c9d9cc39a9b064dd864b08e68938f 9ab5b245ce1c65ef3fe95eedc18d74c3ebd6bb939613a825ffb7; “Qué bandas de frecuencias WiFi hay: Explicación 2.4 GHz, 5 GHz y 6 GHz.” https://www.redeszone.net/tutoriales/redes-wifi/bandas-frecuencias-wi-fi/ (accessed Mar. 23, 2023).; F. G. Landa Barra, “Huella de carbono del transporte urbano para un plan de reducción de gases de efecto invernadero Puno 2021,” Repositorio Institucional - UCV, 2022, Accessed: Nov. 14, 2022. [Online]. https://repositorio.ucv.edu.pe/handle/20.500.12692/88703; S. Ankathi, Z. Lu, G. G. Zaimes, T. Hawkins, Y. Gan, and M. Wang, “Greenhouse gas emissions from the global transportation of crude oil: Current status and mitigation potential,” J Ind Ecol, 2022. https://doi.org/10.1111/jiec.13262; P. D. Faustino M. G., P. D. Florez S. Elkin, and M. Sc Guerrero G. G., “Mercados de energía en Colombia, una introducción,” 2021, Accessed: Nov. 14, 2022. [Online]. https://www.unipamplona.edu.co/unipamplona/portalIG/home_10/recursos/2021/documentos/ 19072021/mercados_energia.pdf.; A. Fernando et al., “Modelo de negocio para la implementación de estaciones de carga para vehículos eléctricos, en la empresa Biored energy,” 2020, Accessed: Nov. 26, 2022. [Online]. https://repository.udistrital.edu.co/handle/11349/28048.; Catagnia Chicaiza, L. D. (2020). Estimación de costos de energía eléctrica para la recarga de vehículos eléctricos basado en la óptima respuesta de la demanda (Bachelor's thesis). http://dspace.ups.edu.ec/handle/123456789/19333.; C. D. C. , Acosta Blanquiceth, J. M. , Chumbe Macana, J. F. , Ortigoza Ulloa, S. D. Palencia Pulido, and Sarmiento Baquero, “Estudio de factibilidad de la instalación de puntos de recarga para vehículos eléctricos en la ciudad de Bogotá,” 2021. https://hdl.handle.net/10882/11290; M. M. Rodríguez, “Impacto. Diseño de estaciones de carga eléctrica sostenible para vehículos eléctricos en Bogotá.,” 2021, Accessed: Nov. 26, 2022. [Online]. Available: http://repositorio.uan.edu.co/handle/123456789/1639.; Departamento Administrativo Nacional de Estadística, url: https://www.dane.gov.co.; Departamento Administrativo Nacional de Estadística https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-ypoblacion/proyecciones-de-poblacion.; Secretaría Distrital de Movilidad. https://www.movilidadbogota.gov.co/; Datos abiertos Bogotá. http://www.ideca.gov.co/recursos/glosario/datos-abiertos/.; Datos abiertos Bogotá. https://datosabiertos.bogota.gov.co/.; OpenStreetMap. https://www.openstreetmap.org/; F. C. Arias, “Estadística Espacial: Fundamentos y aplicación con Sistemas de Información Geográfica,” Revista Cartográfica, no. 105, 2022, doi:10.35424/rcarto.i105.1388. https://doi.org/10.35424/rcarto.i105.1388; V. Gómez Rubio, “Una introducción a la estadística espacial,” Boletín de Estadística e Investigación Operativa, vol. 38, 2022. https://www.seio.es/beio/una-introduccion-a-la-estadistica-espacial/; A. Rangel, A. Sánchez Ipia, W. Siabato, and J. Cely, “Geoestadística aplicada a estudios de contaminación ambiental,” UD y la Geomática, vol. 7 No.2, 2002. https://dialnet.unirioja.es/servlet/articulo?codigo=4797355.; D. Pascual, F. Pla, and S. Sánchez, “Algoritmos de agrupamiento,” Unpublished, 2007. https://repositorio.uci.cu/jspui/handle/123456789/7202; S. Wang, L. Sun, J. Rong, and Z. Yang, “Transit traffic analysis zone delineating method based on Thiessen polygon,” Sustainability (Switzerland), vol. 6, no. 4, 2014, doi:10.3390/su6041821. https://doi.org/10.3390/su6041821; “Geometría computacional,” http://asignatura.us.es/fgcitig/contenidos/gctem3ma.htm.; G. C. Henriques, “Arquitetura algorítmica: Técnicas, processos e fundamentos,” ENANPARQ IV Encontro da Associação Nacional de Pesquisa e Pós-Graduação em Arquitetura e Urbanismo, vol. 1, no. Sessão temática: projeto digital e fabricação na arquitetura, 2016.DOI:10.13140/RG.2.1.3479.3209; L. Jáuregui Álvarez and C. Vázquez Martínez, “MODELO DE NEGOCIO PARA LA GESTIÓN DE PUNTOS DE RECARGA Y ESTACIONAMIENTO NOCTURNO DE TURISMOS ELÉCTRICOS.” https://oa.upm.es/63478/; J. D. Gallo-Sanabria, P. A. Mozuca-Tamayo and R. I. Rincón-Fonseca, “Autonomous trajectory following for an UAV based on computer vision”, Visión electrónica, algo más que un estado sólido, vol. 14, no. 1, 2020; F. Campos Archila, V. Pinzón Saavedra, y F. Robayo Betancourt, “Fuzzy control of quadrotor Ar. Drone 2.0 in a controlled environment”, Vis. Electron., vol. 13, n.º 1, pp. 39–49, feb. 2019.; ] “Generación Eléctrica - Qué es, cómo se produce, renovables”. Concepto. Accedido el 27 de septiembre de 2023. https://concepto.de/generacion-electrica/; A. Gutierres. “Energías renovables: energías para un futuro más seguro”. Organizacion de las Naciones Unidas. Accedido el 1 de septiembre de 2023. https://www.un.org/es/climatechange/raising-ambition/renewable-energy; ] “Datos sobre producción eléctrica %7C Estadísticas mundiales sobre electricidad %7C Enerdata”. Estadísticas energéticas mundiales %7C Enerdata. Accedido el 27 de septiembre de 2023. https://datos.enerdata.net/electricidad/estadisticas-mundiales-produccion-electricidad.html; M. a. tamayo rincon, “PANORAMA ACTUAL DE LA GENERACIÓN HIDRÁULICA EN COLOMBIA Y ANTIOQUIA ANTE EL CRECIMIENTO DE LA DEMANDA DE ENERGÍA”, monografia, Univ. Antioquia, Medellin, 2022.; J. Rosero, L. Morales y D. Pozo, “Fuentes de Generación de Energía Eléctrica Convencional y Renovable a Nivel Mundial”, Rev. Politec., vol. 32, n.º 2, p. 13, 2013.; Malagón, E., 2020. La Hidroelectricidad, La Mayor Fuente De Energía Sostenible. ¡Aquí Te Decimos Por Qué! - Energía Para El Futuro. [Online] Energía para el futuro. Available at: [Accessed 21 October 2020].; Khan, A. A., & Khan, M. R. (2015). A simple and economical design of micro-hydro power generation system. 2015 Power Generation Systems and Renewable Energy Technologies, PGSRET 2015. https://doi.org/10.1109/PGSRET.2015.7312183; Ferro, L. M. C., Gato, L. M. C., & Falcão, A. F. O. (2011). Design of the rotor blades of a mini hydraulic bulb-turbine. Renewable Energy, 36(9), 2395–2403. https://doi.org/10.1016/j.renene.2011.01.037; E. R. Oviedo Ocaña, “Las Hidroeléctricas: efectos en los ecosistemas y en la salud ambiental”, Rev. Univ. Ind. Santander., vol. 50, n.º 3, 2018.; E. Sierra Vargas, A. F. Sierra Alarcon y C. A. Guerrero Fajardo. “Pequeñas y microcentrales hidroeléctricas: alternativa real de generación eléctrica. %7C Informador Técnico”. Revistas SENA. Accedido el 27 de septiembre de 2023. https://revistas.sena.edu.co/index.php/inf_tec/article/view/22/3439#info; Villarreal, J. L. S., Avalos, P. G., Galvan Gonzalez, S. R., & Dominguez Mota, F. J. (2019). Estimate electrical potential of municipal wastewater through a micro-hydroelectric plant. 2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018, Ropec. https://doi.org/10.1109/ROPEC.2018.8661411; Qusay F. Hassan, "An Overview of Enabling Technologies for the Internet of Things," in Internet of Things A to Z: Technologies and Applications, IEEE, 2018, pp.77-112, doi:10.1002/9781119456735.ch3.; Hernandez Sampieri, R., Baptista Lucio, M. d. P., & Fernandez Collado, C. (2014). Metodologia de la investigacion (6a ed.). McGRAW-HILL / INTERAMERICANA EDITORES, S.A. DE C.V.; C M, S., Honnasiddaiah, R., Hindasageri, V., & Madav, V. (2021). Studies on application of vertical axis hydro turbine for sustainable power generation in irrigation channels with different bed slopes. Renewable Energy, 163, 845–857. https://doi.org/10.1016/j.renene.2020.09.015; Elbatran, A. H., Yaakob, O. B., Ahmed, Y. M., & Jalal, M. R. (2015). Novel approach of bidirectional diffuser-augmented channels system for enhancing hydrokinetic power generation in channels. Renewable Energy, 83, 809–819. https://doi.org/10.1016/j.renene.2015.05.038; Lucas D. Spies, E. A. T., Laboratorio. (2015). Diseño y Fabricación de una Turbina Eólica de Eje Vertical Impulsada por Drag. Revista Tecnología y Ciencia, 319–328.; Acevedo L, Lopez J, Sanchez S, (2008) Diseño de una turbina Banki para la recolección de aguas y generación de energía en una propiedad agrícola. Universidad tecnológica de Pereira, ingeniería mecatronica: http://repositorio.utp.edu.co/dspace/bitstream/handle/11059/5770/62124A174.pdf;jsessionid=5 662092429514C805182C7EA731C6F45?sequence=1; Laboratorio de máquinas hidráulicas. (Universidad) (1923). Unidad 6 Turbina De Flujo Transversal O Michell Banki.2, 1–25. https://luiscalderonf.files.wordpress.com/2012/01/turbina-m-banki.pdf; Alfonso, C., & Gutiérrez, P. (2008). La turbina Mochell-Banki y su presencia en Colombia. Avances En Recursos Hidráulicos, 17, 33–42.; Bangi, V. K. T., Chaudhary, Y., Guduru, R. K., Aung, K. T., & Reddy, G. N. (2017). Preliminary investigation on generation of electricity using micro wind turbines placed on a car. International Journal of Renewable Energy Development, 6(1), 75–81. https://doi.org/10.14710/ijred.6.1.75-81; Ochoa, Y., Rodríguez, J., & Martínez, F. (2017). Sistema de regulación y control de carga para aerogenerador de baja potencia. Universidad Distrital Francisco José de Caldas - Facultad Tecnológica.; Hidrotu (empresa) "la turbina hidráulica del bulbo 0.1MW-10MW/la turbina del agua con descarga grande y el agua baja dirigen" Hoja técnica turbina de bulbo hidráulico., Spanish.hydrotu.com, 2020. [Online]. Available: http://spanish.hydrotu.com/china-; La_turbina_hidr_ulica_del_bulbo_0_1mw_10mw_la_turbina_del_agua_con_descarga_gra nde_y_el_agua_baja_di-295887.html. [Accessed: 08- Nov- 2020].; imagen turbina bulbo hidraulico- https://equipo2fae.wordpress.com/turbinas-kaplam/; Turbinas Kaplan. (2012). Recuperado 28 de diciembre de 2020, de EQUIPO2FAE website: https://equipo2fae.wordpress.com/turbinas-kaplam/; ] Vargas, J. A., Clavijo, F. V., & Torres Gómez, C. (2016). Desarrollo del prototipo de un hidrogenerador eléctrico como alternativa de generación de energía limpia en zonas rurales Development of the prototype of an electric hydro generator as an alternative for generating clean energy in rural areas. Ingeniare, 12(20), 91–101.; Naoe, N., Imazawa, A., Takehisa, K., & Nakamura, S. (2018). Bridge structure type micro hydropower-generating system and local region implementation. 2017 International Conference on Electrical, Electronics and System Engineering, ICEESE 2017, 2018-January, 78–83. https://doi.org/10.1109/ICEESE.2017.8298392; Plata, A. (2012). Diseño y desarrollo de un pico-generador hidroeléctrico para producción preindustrial. Universidad de Los Andes, 76.; Delgado Flores, A. F. (2016). Construcción de un convertidor CC-CC tipo reductor orientado a la enseñanza. Universidad Tecnológica de Pereira, 42.; Probe, M., & IoT, E. (2019). Power Consumption Measurements for IoT Applications Application Note. Rohde-Schwarz, 1–16.; Pane, D. N., Fikri, M. EL, & Ritonga, H. M. (2018). Análisis del consumo de energía promedio en dispositivos IoT de baja potencia con Blockchain como solución de seguridad. Journal of Chemical Information and Modeling, 53(9), 1689–1699.; Rose Karen, Eldridge Scott, C. L. (2015). LA INTERNET DE LAS COSAS-UNA BREVE RESEÑA. Internet Society, 83. https://doi.org/10.1007/978-0-85729-103-5_5; Kim, M., Lee, J., Kim, Y., & Song, Y. H. (2018). An analysis of energy consumption under various memory mappings for FRAM-based IoT devices. IEEE World Forum on Internet of Things, WF-IoT 2018 - Proceedings, 2018-January, 574–579. https://doi.org/10.1109/WFIoT.2018.8355212; Bonilla-Fabela Isaias Tavizon-Salazar Arturo Morales-Escobar Melisa Guajardo Muñoz Luz Tania & Laines-Alamina Cristina Isabel, “ISSN: 2448-5101 Año 2 Número 1 Julio 2015 - Junio 2016 2313 IOT, EL INTERNET DE LAS COSAS Y LA INNOVACIÓN DE SUS APLICACIONES”, Trabajo de grado, UANL Sch. Busines, Mexico, 2016.; S. Et. al., “Internet of Things (IoT): A Review”, Turkish J. Comput. Math. Educ. (TURCOMAT), vol. 12, n.º 2, pp. 521–526, abril de 2021. Accedido el 27 de septiembre de 2023, https://doi.org/10.17762/turcomat.v12i2.871; ] J. Flores Zermeño y E. G. Cosio Franco, “Aplicaciones, Enfoques y Tendencias del Internet de las Cosas (IoT): Revisión Sistemática de la Literatura”, Academia J., vol. 13, n.º 9, p. 9, 2021.; C. Chuquimarca, “Análisis comparativo entre arquitecturas de sistemas IoT”, RITI J., vol. 10, n.º 21, p. 16, 2021.; Anonimo. “¿Qué son los sensores IoT y para qué sirven? ¡Descúbrelo! %7C Tokio”. Tokio School. Accedido el 27 de septiembre de 2023, https://www.tokioschool.com/noticias/sensores-IoT/; F. D. Acevedo Garcés, "Diseño de una instalación solar fotovoltaica con capacidad para 3 kilovatios," Universidad Nacional Abierta y a Distancia Colombia, 2016.; M. Caro and R. Alejandro, "Dilemas éticos en la ingeniería," Retrieved 11 de 10 de 2021, from http://repositorio.uchile.cl/handle/2250/113296, 2012.; P. A. Castiblanco F. Luz A., "Trabajo de campo Sistema de Generación," En P. A. Castiblanco F. Luz A., Madrid, Cundinamarca, Cundinamarca, 2021.; T. D. Corcobado, "Instalaciones Solares Fotovoltaicas ciclo formativo de grado medio," Mc Graw Hill, Madrid, España, 2010.; Ministerio de Energía, "Energías Renovables no convencionales," En M. d. Energía. https://www.minenergia.gov.co/energias-renovables-no-convencionales, 2021.; J. Gómez Ramírez, "La energía solar fotovoltaica en Colombia: potenciales, antecedentes y perspectivas," Bogotá, 2017.; C. Guerrero, "Proyecto de Factibilidad para uso de Paneles Solares en Generación Fotovoltaica de Electricidad en el Complejo Habitacional “San Antonio” de Riobamba (Bachelor's thesis)," Riobamba, Ecuador, Ecuador, 2013.; I. S. JORGE, "Instalación y mantenimiento de sistemas solares fotovoltaicos. Capítulo 1, tema 1-2: La célula fotovoltaica. {En línea}. https://311cie.files.wordpress.com/2014/09/tema-1-2-la-celula-fotovoltaica.pdf," 2016.; P. &.-P. Marín-Cots, "En un entorno de 15 minutos: hacia la Ciudad de Proximidad, y su relación con el Covid-19 y la Crisis Climática, el caso de Málaga," Málaga, España, 2020.; Ministerio de Minas y Energía, "Ley 143 de 1994," En i. d. Régimen para la generación. Bogotá. https://www.minenergia.gov.co/documents/10180/667537/Ley_143_1994.pdf, 1994.; Monsolar, "Catálogo de productos," https://www.monsolar.com/bateria-gel-victron12v-165ah.html, 2023.; NASA, "Power Data Access View," https://power.larc.nasa.gov/data-access-viewer/, 2023.; G. C. Orrego, "Serie 3 Solera SE19 ORREGO G. CESAR A. Madrid Cundinamarca," 2019; R. Ortega, "Energías Renovables," Paraninfo, 2000.; UPME-Ideam, "Proyecciones de precios de los energéticos para generación eléctrica enero 2014 – diciembre 2037,"http://www.sipg.gov.co/sipg/documentos/precios_combustibles/Termicas_Marzo_ 2014. pdf, 2014.; WWF, "Glosario ambiental : Acuerdo de París," En WWF, París, Francia. https://www.wwf.org.co/?334976/Glosario-ambiental--Sabes-que-se-pacto-en-elAcuerdo-deParis#:~:text=Colombia%20en%20el%20Acuerdo%20de,de%20emisiones%20nac ionales%20de%202010, 2016.; (n.d.), «Buildings – Analysis - IEA,» 17 Abril 2023. [En línea]. Available: https://www.iea.org/reports/buildings.; C. t. d. l. e. e. España, « Seguridad estructural,» Documento básico SE., España, 2019.; F. Nemry, A. Uihlein, M. Colodel, C. Wetzel, A. Braune, B. Wittstock, I. Hasan, J. Kreißig, N. Gallon, S. Niemeier y Y. Frech, «Options to reduce the environmental impacts of residential buildings in the European Union—Potential and costs,» Energy Build, vol. 42, pp. 976-984, 2010.; Z. Ma, P. Cooper, D. Darly y L. Ledo, «Existing building retrofits: Methodology and stateof-the-art,» Energy Build, pp. 889-902, 2012.; reco2st, «reco2st,» programa de Investigación e Innovación Horizonte 2020 de la Unión Europea, 2020. [En línea]. Available: https://reco2st.eu/innovation/technologies/. [Último acceso: 14 11 2022].; C. o. B. S. Engineers, « Energy Efficiency in Buildings: CIBSE Guide F,» Chartered Institution of Building Services Engineers, 2004.; Objetivos y metas de desarrollo sostenible, «17 objetivos para transformar nuestro mundo,» NACIONES UNIDAS, 2017. [En línea]. Available: https://www.un.org/sustainabledevelopment/es/sustainable-development-goals/. [Último acceso: Noviembre 2022].; M. Santamouris y K. Vasilakopoulou, «Present and future energy consumption of buildings: Challenges and opportunities towards decarbonisation,» Electronics and Energy, vol. 1, 2021.; n.d, «Energy Efficiency 2019 – Analysis - IEA,» 17 Abril 2023. [En línea]. Available: https://www.iea.org/reports/energy-efficiency-2019.; L. Biardeau, L. Davis, P. Gertler y C. Wolfram, «Heat exposure and global air conditioning,» Nat Sustain, vol. 3, p. 25–28, 2020.; MITMA, «Documento Básico HS Salubiridad,» Ministerio de Transporte, Movilidad y Agenda Urbana, 2022.; J. Pradillo, ENFRIAMIENTO ADIABÁTICO INDIRECTO MEDIANTE CICL0 DE MAISOTSENKO Y APLICACIONES, wolf, 2015.; F. Rabadán, Evaluación de medidas de eficiencia energética en el, Sevilla: Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, 2021.; ABECE, «teoria sobre climatización adiabática,» Enero 2021. [En línea]. Available: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://asociacionbioclimatica.es/wpcontent/uploads/2021/01/TECNOLOGIAS-ADIABA%CC%81TICAS.pdf. [Último acceso: Noviembre 2022].; J. M. Arroyo and F. J. Fernández, “A genetic algorithm for power system vulnerability analysis under multiple contingencies,” Stud. Comput. Intell., vol. 482, pp. 41–68, 2013, doi:10.1007/978-3-642-37838-6_2.; D. K. Mishra, M. J. Ghadi, A. Azizivahed, L. Li, and J. Zhang, “A review on resilience studies in active distribution systems,” Renew. Sustain. Energy Rev., vol. 135, no. March 2020, 2021, doi:10.1016/j.rser.2020.110201.; J. Colombi, John M.; Miller, Michael E.; Schneider, Michael; McGrogan, Jason; Long, David S.; Plaga, “Towards Affordably Adaptable and Effective Systems,” Syst. Eng., vol. 14, no. 3, pp. 305–326, 2012, doi:10.1002/sys.; B. De Ataque and R. D. L. Sistemas, “A Bilevel Attacker-Defender Model for Enhancing Power Systems Resilience with Distributed Generation,” Sci. Tech., vol. 25, no. 4, pp. 540–547, 2020, doi:10.22517/23447214.23721.; P. H. Corredor and M. E. Ruiz, “Mitigating the Impact of Terrorist Activity on Colombia’s Power System,” IEEE Power Energy Mag., vol. 9, no. 2, pp. 59–66, 2011.; S. Cai, Y. Xie, Q. Wu, and Z. Xiang, “Robust MPC-based microgrid scheduling for resilience enhancement of distribution system,” Int. J. Electr. Power Energy Syst., vol. 121, no. April, p. 106068, 2020, doi:10.1016/j.ijepes.2020.106068.; S. N. Emenike and G. Falcone, “A review on energy supply chain resilience through optimization,” Renew. Sustain. Energy Rev., vol. 134, no. September, p. 110088, 2020, doi:10.1016/j.rser.2020.110088.; Z. Wan, Y. Mahajan, B. W. Kang, T. J. Moore, and J. H. Cho, “A Survey on Centrality Metrics and Their Network Resilience Analysis,” IEEE Access, vol. 9, pp. 104773–104819, 2021, doi:10.1109/ACCESS.2021.3094196.; L. Lotero and R. G. Hurtado, “Vulnerabilidad De Redes Complejas Y Una Revisión De La Literatura Vulnerability of Complex Networks and Urban Transportation Applications : a Literature Review,” Rev. EIA, vol. 11, no. 11, pp. 67–78, 2015.; T. Conferencia, M. D. E. Las, and R. D. E. Desastres, “Tercera Conferencia Mundial de las Naciones Unidas sobre la Reducción del Riesgo de Desastres,” 2015.; D. Sage, P. Fussey, and A. Dainty, “Securing and scaling resilient futures: neoliberalization, infrastructure, and topologies of power,” Environ. Plan. D Soc. Sp., vol. 33, no. 3, pp. 494–511, 2015, doi:10.1068/d14154p.; J. Pilatásig Lasluisa, “Resiliencia de Sistemas Eléctricos de Potencia mediante la Conmutación de Líneas de Transmisión – Estado del arte,” I+D Tecnológico, vol. 16, no. 2, 2020, doi:10.33412/idt.v16.2.2834.; B. M. Qu, T. Ding, L. Huang, and X. Wu, “Toward a Global Green Smart Microgrid,” pp. 55–69, 2020.; T. Khalili, A. Bidram, and M. J. Reno, “Impact study of demand response program on the resilience of dynamic clustered distribution systems,” IET Gener. Transm. Distrib., vol. 14, no. 22, pp. 5230–5238, 2020, doi:10.1049/iet-gtd.2020.0068.; J. Wu, H. Z. Deng, Y. J. Tan, and D. Z. Zhu, “Vulnerability of complex networks under intentional attack with incomplete information,” J. Phys. A Math. Theor., vol. 40, no. 11, pp. 2665–2671, 2007, doi:10.1088/1751-8113/40/11/005.; M. Azeroual, T. Lamhamdi, H. El Moussaoui, and H. El Markhi, “Simulation tools for a smart grid and energy management for microgrid with wind power using multi-agent system,” Wind Eng., vol. 44, no. 6, pp. 661–672, 2020, doi:10.1177/0309524X19862755.; Y. Wang et al., “Coordinating multiple sources for service restoration to enhance resilience of distribution systems,” IEEE Trans. Smart Grid, vol. 10, no. 5, pp. 5781–5793, 2019, doi:10.1109/TSG.2019.2891515.; Q. Shi et al., “Network reconfiguration and distributed energy resource scheduling for improved distribution system resilience,” Int. J. Electr. Power Energy Syst., vol. 124, no. March 2020, p. 106355, 2021, doi:10.1016/j.ijepes.2020.106355.; K. Eshghi, B. K. Johnson, and C. G. Rieger, “Metrics required for power system resilient operations and protection,” Proc. - 2016 Resil. Week, RWS 2016, pp. 200–203, 2016, doi:10.1109/RWEEK.2016.7573333.; C. Ji, Y. Wei, and H. V. Poor, “Resilience of Energy Infrastructure and Services: Modeling, Data Analytics, and Metrics,” Proc. IEEE, vol. 105, no. 7, pp. 1354–1366, 2017, doi:10.1109/JPROC.2017.2698262.; D. J. M. Palacios, E. R. Trujillo, and J. M. López-Lezama, “Vulnerability analysis to maximize the resilience of power systems considering demand response and distributed generation,” Electron., vol. 10, no. 12, pp. 1–22, 2021, doi:10.3390/electronics10121498.; M. Bruneau et al., “A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities,” Earthq. Spectra, vol. 19, no. 4, pp. 733–752, 2003, doi:10.1193/1.1623497.; K. S. A. Sedzro, A. J. Lamadrid, and L. F. Zuluaga, “Allocation of Resources Using a Microgrid Formation Approach for Resilient Electric Grids,” IEEE Trans. Power Syst., vol. 33, no. 3, pp. 2633–2643, 2018, doi:10.1109/TPWRS.2017.2746622.; L. Yang, Y. Xu, H. Sun, M. Chow, and J. Zhou, “A multiagent system based optimal load restoration strategy in distribution systems,” Int. J. Electr. Power Energy Syst., vol. 124, no. May 2020, p. 106314, 2021, doi:10.1016/j.ijepes.2020.106314.; «Logra energía eólica a nivel mundial 1 TW de capacidad instalada», Energía Hoy. Accedido: 22 de agosto de 2023. [En línea]. Disponible en: https://energiahoy.com/2023/06/16/logra-energia-eolica-a-nivel-mundial-1-tw-de-capacidadinstalada/; P. M. Medina, «Colombia es uno de los países de la OCDE que más energía renovable genera», infobae. Accedido: 16 de agosto de 2023. [En línea]. Disponible en: https://www.infobae.com/colombia/2023/02/15/colombia-es-uno-de-los-paises-de-la-ocdeque-mas-energia-renovable-genera/; «Vista de Generador lineal para un generador eólico de baja potencia, selección, diseño y simulación en comsol multiphysic». Accedido: 16 de agosto de 2023. [En línea]. Disponible en: https://revistas.udistrital.edu.co/index.php/vinculos/article/view/18620/17571; Mohan Ned, Undeland Tore, Robbins William, ELECTRONICA DE POTENCIA: Convertidores, aplicaciones y diseño, 3.a ed. Mc Graw Hill, 2009.; «Simscape Electrical». Accedido: 21 de julio de 2023. [En línea]. Disponible en: https://la.mathworks.com/products/simscape-electrical.html; M. H. Rashid, Electrónica de Potencia, 2.a ed. PRENTICE HALL HISPANOAMERICANA, S.A, 1993.; «Introducción a la identificación de sistemas», TÉCNICA INDUSTRIAL. Accedido: 24 de agosto de 2023. [En línea]. Disponible en: https://www.tecnicaindustrial.es/introduccion-a-laidentificacion-de-sistemas/; «System Identification Toolbox». Accedido: 24 de agosto de 2023. [En línea]. Disponible en: https://la.mathworks.com/products/sysid.html; L. J. Marín y V. M. Alfaro, «Sintonización de controladores por ubicación de polos y ceros», 2007.; S. C, «CONTROLADOR PI - Asignación de Polos [FÁCIL - Aprende]», Control Automático Educación. Accedido: 24 de agosto de 2023. [En línea]. Disponible en: https://controlautomaticoeducacion.com/control-realimentado/controlador-pi-por-asignacionde-polos/; «CONTROLADOR PI - Asignación de Polos [FÁCIL - Aprende]». Accedido: 24 de agosto de 2023. [En línea]. Disponible en: https://controlautomaticoeducacion.com/controlrealimentado/controlador-pi-por-asignacion-de-polos/; S. C, « Control Fuzzy - Mamdani - Simulink - [agosto, 2023 ]», Control Automático Educación. Accedido: 24 de agosto de 2023. [En línea]. Disponible en: https://controlautomaticoeducacion.com/control-realimentado/control-fuzzy-mamdanisimulink/; Agencia Internacional de Energía (AIE), "Perspectivas de tecnología energética 2020", AIE, 2020.; MA Ortega-Vázquez, MV Salas y KE Yeager, "Recursos energéticos distribuidos y su integración en el sistema de energía eléctrica", Proc. IEEE, vol. 99, núm. 1, págs. 28–39, enero de 2011.; N. Hatziargyriou, H. Asano, R. Iravani y C. Marnay, "Microgrids", IEEE Power Energy Mag., vol. 5, núm. 4, págs. 78–94, julio de 2007.; R. Pérez-García, F. González-Longatt y S. Carneiro, "Review of Distributed Energy Resources Integration in the IEEE Standards", en 2020 IEEE PES Transmission & Distribution Conference and Exposition (T&D), 2020; AS Al-Mohammed, RMO Al-Mohammed y M. Al- Mansoori, "Impacto de los recursos energéticos distribuidos en la calidad de la energía en las redes inteligentes: una revisión integral", Energías, vol. 13, núm. 7, pág. 1580, 2020.; S. A. Abbas, S. F. Hasan, D. R. Shin, “Analyzing the Integration of Distributed Generation into Smartgrids,” College of Information and Communications Engineering. Sungkyunkwan University. IEEE, 2015); G. Gross, J. Heinemann y F. Siefert, "Integración de energías renovables y su impacto en las operaciones de red",en 2010 IEEE PES Innovative Smart Grid Technologies, 2010.; K. Wang, Z. Xu y H. Wang, "Estándar IEEE y su aplicación en la regulación de microrredes", en 2012 Tercera Conferencia Internacional sobre Control Inteligente y Procesamiento de Información, 2012.; HY Kim, YS Cho y SS Kim, "Una revisión de la investigación sobre modelado y análisis de microrredes", Renew. Sostener. Energía Rev., vol. 59, págs. 1634-1640, 2016.; SR Mohanty, SN Singh y A. Kishor, "Una revisión de los métodos de detección de islas para la generación distribuida", Renew. Sostener. Energía Rev., vol. 13, núm. 8, págs. 1801- 1818, 2009.; ] F. Katiraei, MR Iravani y PW Lehn, "Operación autónoma de microredes durante y después del proceso de aislamiento", IEEE Trans. Entrega de energía, vol. 20, núm. 1, págs. 248-257.; M. Stadler et al., "Asignación y envío óptimos de recursos de energía distribuida: una revisión", IEEE Trans. Sistema de energía, vol. 22, núm. 1, págs. 107-116, 2007.; P. Palensky y D. Dietrich, "Gestión del lado de la demanda: respuesta a la demanda, sistemas de energía y cargas inteligentes", IEEE Trans. Indiana Informática, vol. 7, núm. 3, págs. 381-388, 2011.; CA Silva, SJ Rider y CS Yim, "Sistemas de almacenamiento de energía eléctrica: un análisis comparativo del costo del ciclo de vida", Renew. Sostener. Energía Rev., vol. 14, núm. 9, págs. 2717-2726, 2010.; E. Muljadi, CP Butterfield, A. Ellis y J. Meiman, "EnergyStorage for Stabilization of Wind Power", IEEE Trans. Solicitud de Indiana, vol. 37, núm. 1, págs. 272-280, 2001.; L. Zhong, X. Fang, J. Chen y Z. Zhang, "Regulación de carga de recursos energéticos distribuidos mediante controlpredictivo de modelos", en 2015 IEEE Energy Conversion Congress and Exposition (ECCE), 2015.; P. Deane, G. O'Gallachoir y B. Ó. Gallachóir, "Revisión tecnoeconómica de una planta de almacenamiento de energía hidráulica por bombeo nueva y existente", Renovar. Sostener. Energía Rev., vol. 14, núm. 4, págs. 1293-1302, 2010.; E. Marín y P. Gómez, “Criterios e indicadores para la evaluación de la sostenibilidad de los sistemas energéticos”, Energía, vol. 32, núm. 12, págs. 2173-2181, 2007.; NK Roy, MT Naayagi y AM Ismail, "Análisis tecnoeconómico del sistema híbrido de almacenamiento deenergía para una planta de energía fotovoltaica independiente",Renew. Sostener. Energía Rev., vol. 69, págs. 1246-1256, 2017.; EG Talbi y K. Chekired, "Análisis económico y técnico de un sistema híbrido compuesto por paneles fotovoltaicos y baterías para un consumidor doméstico en Argelia", Energy Convers. Gestionar., vol. 47, núm. 18-19, págs. 3396-3409, 2006.; S. Deng, S. Zhong, Y. Fan y J. Du, "Operación óptima del almacenamiento de energía integrado y electrodomésticos inteligentes en microrredes considerando la respuesta a la demanda", IEEE Trans. Red inteligente, vol. 7, núm. 6, págs. 2831-2841, 2016.; https://hdl.handle.net/11349/40350

  9. 9
  10. 10

    Alternate Title: Predicción de la Producción de Residuos con incertidumbre en la Ciudad inteligente mediante neuroevolución profunda. (Spanish)

    Zdroj: Revista Facultad de Ingeniería Universidad de Antioquia; Oct-Dec2019, Issue 93, p128-138, 11p

    Geografický termín: SPAIN

  11. 11

    Alternate Title: Problema de programación fraccionaria lineal difusa utilizando el método lexicográfico. (Spanish)
    Задача нечеткого дробно-линейного программирования с использованием лексикографического метода. (Russian)
    Проблем фази линеарног фракционог програмирања помоћу лексикографског метода. (Serbian)

    Zdroj: Military Technical Courier / Vojnotehnicki Glasnik; Jul-Sep2024, Vol. 72 Issue 3, p965-978, 14p

  12. 12
  13. 13

    Alternate Title: Metaheuristics for Multicriteria Decision-Making: A Systematic Literature Review and Research Opportunities. (English)
    Metaheurística para la toma de decisiones multicriterio: revisión sistemática de la literatura y oportunidades de investigación. (Spanish)

    Zdroj: Innovar: Revista de Ciencias Administrativas y Sociales; abr-jun2025, Vol. 35 Issue 96, p1-33, 33p

  14. 14
  15. 15
  16. 16

    Autori: Rusu, Adina

    Zdroj: Bulletin of the Polytechnic Institute of Iași, Machine Construction Section; Mar2025, Vol. 71 Issue 1, p59-71, 13p

  17. 17
  18. 18
  19. 19
  20. 20

    Popis súboru: xv, 158 páginas; application/pdf

    Relation: Ahmadi-Javid, A., & Seddighi, A. H. (2012). A location-routing-inventory model for designing multisource distribution networks. Engineering Optimization, 44(6), 637–656. https://doi.org/10.1080/0305215X.2011.600756; Ahmadi Javid, A., & Azad, N. (2010). Incorporating location, routing and inventory decisions in supply chain network design. Transportation Research Part E: Logistics and Transportation Review, 46(5), 582–597. https://doi.org/10.1016/j.tre.2009.06.005; Alikhani, R., Torabi, S. A., & Altay, N. (2021). Retail supply chain network design with concurrent resilience capabilities. International Journal of Production Economics, 234. https://doi.org/10.1016/j.ijpe.2021.108042; Aloui, A., Hamani, N., Derrouiche, R., & Delahoche, L. (2021). Assessing the benefits of horizontal collaboration using an integrated planning model for two-echelon energy efficiency-oriented logistics networks design. International Journal of Systems Science: Operations and Logistics. https://doi.org/10.1080/23302674.2021.1887397; Amaruchkul, K. (2021). Planning migrant labor for green sugarcane harvest: A stochastic logistics model with dynamic yield prediction. Computers and Industrial Engineering, 154. https://doi.org/10.1016/j.cie.2020.107016; Ambrosino, D., & Grazia Scutellà, M. (2005). Distribution network design: New problems and related models. European Journal of Operational Research, 165(3), 610–624. https://doi.org/10.1016/J.EJOR.2003.04.009; Aravendan, M., & Panneerselvam, R. (2014). Literature review on network design problems in closed loop and reverse supply chains. Intelligent Information Management, 2014.; Asadi, E., Habibi, F., Nickel, S., & Sahebi, H. (2018). A bi-objective stochastic location-inventory-routing model for microalgae-based biofuel supply chain. Applied Energy, 228(July), 2235–2261. https://doi.org/10.1016/j.apenergy.2018.07.067; Awudu, I., & Zhang, J. (2012). Uncertainties and sustainability concepts in biofuel supply chain management: A review. Renewable and Sustainable Energy Reviews, 16(2), 1359–1368. https://doi.org/http://dx.doi.org/10.1016/j.rser.2011.10.016; Ayoughi, H., Dehghani Podeh, H., Raad, A., & Talebi, D. (2020). Providing an Integrated Multi-Objective Model for Closed-Loop Supply Chain under Fuzzy Conditions with Upgral Approach. International Journal of Nonlinear Analysis and Applications, 11(1), 107–136.; Babagolzadeh, M., Shrestha, A., Abbasi, B., & Zhang, Y. (2020). Sustainable cold supply chain management under demand uncertainty and carbon tax regulation. Transportation Research Part D, 80, 102245. https://doi.org/10.1016/j.trd.2020.102245; Bag, S., Dhamija, P., Bryde, D. J., & Singh, R. K. (2022). Effect of eco-innovation on green supply chain management, circular economy capability, and performance of small and medium enterprises. Journal of Business Research, 141, 60–72. https://doi.org/10.1016/j.jbusres.2021.12.011; Bagherinejad, J., & Shoeib, M. (2018). Dynamic capacitated maximal covering location problem by considering dynamic capacity. International Journal of Industrial Engineering Computations, 9(2), 249–264. https://doi.org/10.5267/j.ijiec.2017.5.004; Banasik, A., Kanellopoulos, A., Claassen, G. D. H., Bloemhof-Ruwaard, J. M., & van der Vorst, J. G. A. J. (2017). Closing loops in agricultural supply chains using multi-objective optimization: A case study of an industrial mushroom supply chain. International Journal of Production Economics, 183, 409–420. https://doi.org/10.1016/j.ijpe.2016.08.012; Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018). Agribusiness supply chain risk management: A review of quantitative decision models. Omega, 79, 21–42. https://doi.org/10.1016 / j.omega.2017.07.005; Bera, T., Inglett, K. S., Inglett, P. W., Vardanyan, L., Wilkie, A. C., O’Connor, G. A., & Reddy, K. R. (2021). Comparing first- and second-generation bioethanol by-products from sugarcane: Impact on soil carbon and nitrogen dynamics. Geoderma, 384. https://doi.org/10.1016/j.geoderma.2020.114818; Beske, P., Land, A., & Seuring, S. (2014). Sustainable supply chain management practices and dynamic capabilities in the food industry: A critical analysis of the literature. International Journal of Production Economics, 152, 131–143. https://doi.org/10.1016/j.ijpe.2013.12.026; Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 260. https://doi.org/10.1016/j.jclepro.2020.120842; Bonilla-Hermosa, V. A., Duarte, W. F., & Schwan, R. F. (2014). Utilization of coffee by-products obtained from semi-washed process for production of value-added compounds. Bioresource Technology, 166, 142–150. https://doi.org/10.1016/j.biortech.2014.05.031; Boostani, A., Jolai, F., & Bozorgi-Amiri, A. (2021). Designing a sustainable humanitarian relief logistics model in pre-and postdisaster management. International Journal of Sustainable Transportation, 15(8), 604–620.; Borodin, V., Bourtembourg, J., Hnaien, F., & Labadie, N. (2016). Handling uncertainty in agricultural supply chain management: A state of the art. European Journal of Operational Research, 254(2), 348–359. https://doi.org/10.1016/j.ejor.2016.03.057; Cadena, E., Rocca, F., Gutierrez, J. A., & Carvalho, A. (2019). Social life cycle assessment methodology for evaluating production process design : Biore fi nery case study. Journal of Cleaner Production, 238, 117718. https://doi.org/10.1016/j.jclepro.2019.117718; Cenicafé. (2016). Manejo de Subproductos. https://www.cenicafe.org/es/index.php/cultivemos_cafe/manejo_de_subproductos; Choi, I. S., Wi, S. G., Kim, S.-B., & Bae, H.-J. (2012). Conversion of coffee residue waste into bioethanol with using popping pretreatment. Bioresource Technology, 125, 132–137. https://doi.org/10.1016/j.biortech.2012.08.080; Christopher, M. (2007). New directions in logistics. Waters, D., Global Logistics: New Directions in Supply Chain Management, London, Kogan Page Limited, 21–32.; Conpes. (2008). C o n p e s 3510. Lineamientos de política para promover la producción sostenible de Biocombustibles en Colombia. http://www.minminas.gov.co/minminas/downloads/UserFiles/File/Conpes 3510.pdf; Conpes. (2022). CONPES 4075. Política de transición energética. https://colaboracion.dnp.gov.co/CDT/Conpes/Económicos/4075.pdf; Correa, D. F., Beyer, H. L., Possingham, H. P., Fargione, J. E., Hill, J. D., & Schenk, P. M. (2021). Microalgal biofuel production at national scales: Reducing conflicts with agricultural lands and biodiversity within countries. Energy, 215. https://doi.org/10.1016/j.energy.2020.119033; Čuček, L., Martín, M. J. P., Grossmann, I. E., & Kravanja, Z. (2012). Multi-objective optimization of a biorefinery’s supply network. AIChE 2012 - 2012 AIChE Annual Meeting, 1.; da Silva, C., Barbosa-Póvoa, A. P., & Carvalho, A. (2020). Environmental monetization and risk assessment in supply chain design and planning. Journal of Cleaner Production, 270. https://doi.org/10.1016/j.jclepro.2020.121552; Duarte, A., Sarache, W., & Costa, Y. (2014). A facility-location model for biofuel plants: Applications in the Colombian context. Energy, 72, 476–483. https://doi.org/10.1016/j.energy.2014.05.069; Duarte, A., Sarache, W., & Costa, Y. (2016). Biofuel supply chain design from Coffee Cut Stem under environmental analysis. Energy, 100, 321–331. https://doi.org/10.1016/J.ENERGY.2016.01.076; Echeverry, M. (2009). Algoritmos evolutivos y técnicas bio-inspiradas. De la teoría a la práctica. Universidad tecnológica de Pereira Pereira.; Eskandarpour, M., Dejax, P., Miemczyk, J., & Péton, O. (2015). Sustainable supply chain network design: An optimization-oriented review. Omega (United Kingdom), 54, 11–32. https://doi.org/10.1016/j.omega.2015.01.006; Fallah-Tafti, A., Vahdatzad, M. A., & Sadegheiyeh, A. (2019). A comprehensive mathematical model for a location-routing-inventory problem under uncertain demand: A numerical illustration in cash-in-transit sector. International Journal of Engineering, Transactions B: Applications, 32(11), 1634 – 1642. https://doi.org/10.5829/ije.2019.32.11b.15; FAO. (2013). Food wastage footprint: impacts on natural resources: summary report. Food \& Agriculture Org.; Fatemi Ghomi, S. M. T., & Asgarian, B. (2019). Development of metaheuristics to solve a transportation inventory location routing problem considering lost sale for perishable goods. Journal of Modelling in Management, 14(1), 175–198. https://doi.org/10.1108/JM2-05-2018-0064; Fedebiocombustibles. (2022). Fedebiocombustibles. https://fedebiocombustibles.com/2022/06/01/4-contribuciones-clave-del-sector-de-los-biocombustibles-ante-los-compromisos-del-cop-26-2/; Feitó-Cespón, M., Costa, Y., Pishvaee, M. S., & Cespón-Castro, R. (2021). A fuzzy inference based scenario building in two-stage optimization framework for sustainable recycling supply chain redesign. Expert Systems with Applications, 165. https://doi.org/10.1016/j.eswa.2020.113906; FNC. (2013a). Familias cafeteras en Colombia. http://www.federaciondecafeteros.org/particulares/es/nuestros_caficultores; FNC. (2013b). La decisión tranquila de zoquear hoy un cafetal - Federación Nacional de Cafeteros. https://federaciondecafeteros.org/wp/blog/la-decision-tranquila-de-zoquear-hoy-un-cafetal/; FNC. (2022). Precios, área y producción de café. https://federaciondecafeteros.org/wp/estadisticas-cafeteras/; Gamborg, C., Millar, K., Shortall, O., & Sandøe, P. (2012). Bioenergy and Land Use: Framing the Ethical Debate. Journal of Agricultural and Environmental Ethics, 25(6), 909–925. http://www.scopus.com/inward/record.url?eid=2-s2.0-84869082138&partnerID=40&md5=114a56e8989289127258d3e34e663bf0; Ghelichi, Z., Saidi-Mehrabad, M., & Pishvaee, M. S. (2018). A stochastic programming approach toward optimal design and planning of an integrated green biodiesel supply chain network under uncertainty: A case study. Energy, 156, 661–687. https://doi.org/10.1016/j.energy.2018.05.103; Gholipour, S., Ashoftehfard, A., & Mina, H. (2020). Green supply chain network design considering inventory-location-routing problem: A fuzzy solution approach. International Journal of Logistics Systems and Management, 35(4), 436–452. https://doi.org/10.1504/IJLSM.2020.106272; Ghorashi, S. B., Hamedi, M., & Sadeghian, R. (2020). Modeling and optimization of a reliable blood supply chain network in crisis considering blood compatibility using MOGWO. Neural Computing and Applications, 32(16), 12173 – 12200. https://doi.org/10.1007/s00521-019-04343-1; Govindan, K., Jafarian, A., Khodaverdi, R., & Devika, K. (2014). Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. International Journal of Production Economics, 152, 9–28. https://doi.org/10.1016/j.ijpe.2013.12.028; Govindan, K., Mina, H., Esmaeili, A., & Gholami-Zanjani, S. M. (2020). An Integrated Hybrid Approach for Circular supplier selection and Closed loop Supply Chain Network Design under Uncertainty. Journal of Cleaner Production, 242. https://doi.org/10.1016/j.jclepro.2019.118317; GRI. (2016). Global Reporting Initiative. In GRI 306: Effluents and Waste. GRI Standards. https://www.globalreporting.org/standards/gri-standards-download-center/; Guerrero, W. J., Prodhon, C., Velasco, N., & Amaya, C. A. (2013). Hybrid heuristic for the inventory location-routing problem with deterministic demand. International Journal of Production Economics, 146(1), 359–370. https://doi.org/10.1016/j.ijpe.2013.07.025; Habibi, F., Asadi, E., & Sadjadi, S. J. (2017). Developing a location-inventory-routing model using METRIC approach in inventory policy. Uncertain Supply Chain Management, 5(4), 337–358. https://doi.org/10.5267/j.uscm.2017.4.003; Habibi, F., Asadi, E., & Sadjadi, S. J. (2018). A location-inventory-routing optimization model for cost effective design of microalgae biofuel distribution system: A case study in Iran. Energy Strategy Reviews, 22(April 2017), 82–93. https://doi.org/10.1016/j.esr.2018.08.006; Hajirasouli, A., & Kumarasuriyar, A. (2016). The social dimention of sustainability: Towards some definitions and analysis. Journal of Social Science for Policy Implications, 4(2), 23–34.; Hernández-Sampieri, R., Fernández Collado, C., Baptista Lucio, P., & others. (2018). Metodología de la investigación (Vol. 4). McGraw-Hill Interamericana México.; Ho, D. P., Ngo, H. H., & Guo, W. (2014). A mini review on renewable sources for biofuel. Bioresource Technology, 169(0), 742–749. https://doi.org/http://dx.doi.org/10.1016/j.biortech.2014.07.022; Hu, J., & Li, X. (2022). Construction and optimization of green supply chain management mode of agricultural enterprises in the digital economy. International Journal of Information Systems and Supply Chain Management, 15(2), 1–18. https://doi.org/10.4018/IJISSCM.287864; Huang, E., & Goetschalckx, M. (2014). Strategic robust supply chain design based on the Pareto-optimal tradeoff between efficiency and risk. European Journal of Operational Research, 237(2), 508–518. https://doi.org/10.1016/j.ejor.2014.02.038; Hurford, A. P., Huskova, I., & Harou, J. J. (2014). Using many-objective trade-off analysis to help dams promote economic development, protect the poor and enhance ecological health. Environmental Science & Policy, 38, 72–86. https://doi.org/10.1016/J.ENVSCI.2013.10.003; Huysman, S., Sala, S., Mancini, L., Ardente, F., Alvarenga, R. A. F., De Meester, S., Mathieux, F., & Dewulf, J. (2015). Toward a systematized framework for resource efficiency indicators. Resources, Conservation and Recycling, 95, 68–76. https://doi.org/10.1016/j.resconrec.2014.10.014; ICO. (2020). International Coffee Organization. https://www.ico.org/; ICO. (2022). Total production of exporting countries. http://www.ico.org/prices/po.htm; IPCC. (2007). Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (L. A. M. B. Metz, O.R. Davidson, P.R. Bosch, R. Dave (ed.)). https://archive.ipcc.ch/publications_and_data/ar4/wg3/en/contents.html; IPCC. (2011). Summary for Policymakers. In: IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation (C. von S. O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner, T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer (ed.)).; IPCC. (2018). Summary for Policymakers. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to (V. Masson-Delmotte, P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P. R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J. B. R. Matthews, Y. Chen, X. Zhou, M. I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, & T. Waterfield (eds.)).; IPCC. (2019). Summary for Policymakers. In: Climate Change and Land: an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems ((eds.)]. In press. [P.R. Shukla, J. Skea, E. Calvo Buendia, V. Masson-Delmotte, H.- O. Pörtner, D. C. Roberts, P. Zhai, R. Slade, S. Connors, R. van Diemen, M. Ferrat, E. Haughey, S. Luz, S. Neogi, M. Pathak, J. Petzold, J. Portugal Pereira, P. Vyas, E. Huntley, K. Kissick, (ed.)).; Ivanov, B., & Stoyanov, S. (2016). A mathematical model formulation for the design of an integrated biodiesel-petroleum diesel blends system. Energy, 99. https://doi.org/10.1016/j.energy.2016.01.038; Jena, S. D., Cordeau, J.-F., & Gendron, B. (2016). Solving a dynamic facility location problem with partial closing and reopening. Computers and Operations Research, 67, 143–154. https://doi.org/10.1016/j.cor.2015.10.011; Jiménez, J. E., & Hernández, S. (2002). Marco conceptual de la cadena de suministro : un nuevo enfoque logístico. In Instituto Mexicano del Transporte (Issue 215). http://www.elmayorportaldegerencia.com/Documentos/Cadena Suministros/[PD] Documentos - Un nuevo enfoque logistico.pdf; Jonkman, J., Barbosa-Póvoa, A. P., & Bloemhof, J. M. (2019). Integrating harvesting decisions in the design of agro-food supply chains. European Journal of Operational Research, 276(1), 247–258. https://doi.org/10.1016/j.ejor.2018.12.024; Kamble, S. S., Gunasekaran, A., & Gawankar, S. A. (2020). Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications. International Journal of Production Economics, 219, 179–194. https://doi.org/10.1016/j.ijpe.2019.05.022; Karakostas, P., Sifaleras, A., & Georgiadis, M. C. (2020). Adaptive variable neighborhood search solution methods for the fleet size and mix pollution location-inventory-routing problem. Expert Systems with Applications, 153. https://doi.org/10.1016/j.eswa.2020.113444; Kaya, O., & Ozkok, D. (2020). A Blood Bank Network Design Problem with Integrated Facility Location, Inventory and Routing Decisions. Networks and Spatial Economics, 20(3), 757 – 783. https://doi.org/10.1007/s11067-020-09500-x; Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. https://doi.org/10.1126 / science.220.4598.671; Kumar, M., Tiwari, M. K., Wong, K. Y., Govindan, K., & Kuah, C. T. (2014). Evaluating reverse supply chain efficiency: Manufacturer’s perspective. Mathematical Problems in Engineering, 2014. https://doi.org/10.1155/2014/901914; Lahri, V., Shaw, K., & Ishizaka, A. (2021). Sustainable supply chain network design problem: Using the integrated BWM, TOPSIS, possibilistic programming, and ε-constrained methods. Expert Systems with Applications, 168. https://doi.org/10.1016/j.eswa.2020.114373; Lee, S., Park, S. J., & Seshadri, S. (2017). Plant location and inventory level decisions in global supply chains: Evidence from Korean firms. European Journal of Operational Research, 262(1), 163–179. https://doi.org/10.1016/j.ejor.2017.03.044; Liu, S. C., & Lee, S. B. (2003). A two-phase heuristic method for the multi-depot location routing problem taking inventory control decisions into consideration. The International Journal of Advanced Manufacturing Technology, 22(11–12), 941–950. https://doi.org/10.1007/s00170-003-1639-5; Liu, Y., Ma, L., & Liu, Y. (2021). A novel robust fuzzy mean-UPM model for green closed-loop supply chain network design under distribution ambiguity. Applied Mathematical Modelling, 92, 99–135. https://doi.org/10.1016/j.apm.2020.10.042; Maass, K. L., Daskin, M. S., & Shen, S. (2016). Mitigating hard capacity constraints with inventory in facility location modeling. IIE Transactions (Institute of Industrial Engineers), 48(2), 120–133. https://doi.org/10.1080/0740817X.2015.1078015; Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, 196(2), 401–412. https://doi.org/10.1016/j.ejor.2008.05.007; Meredith, J. R., Raturi, A., Amoako-Gyampah, K., & Kaplan, B. (1989). Alternative research paradigms in operations. Journal of Operations Management, 8(4), 297–326. https://doi.org/10.1016/0272-6963(89)90033-8; Messmann, L., Zender, V., Thorenz, A., & Tuma, A. (2020). How to quantify social impacts in strategic supply chain optimization: State of the art. Journal of Cleaner Production, 257, 120459. https://doi.org/10.1016 / j.jclepro.2020.120459; Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. The Journal of Chemical Physics, 21(6), 1087–1092.; Mirhashemi, M. S., Mohseni, S., Hasanzadeh, M., & Pishvaee, M. S. (2018). Moringa oleifera biomass-to-biodiesel supply chain design: An opportunity to combat desertification in Iran. Journal of Cleaner Production, 203, 313–327. https://doi.org/10.1016/j.jclepro.2018.08.257; Monemi, R. N., Gelareh, S., Nagih, A., & Jones, D. (2021). Bi-objective load balancing multiple allocation hub location: a compromise programming approach. Annals of Operations Research, 296(1), 363–406.; Morales-Chavez, M. M., Costa, Y., & Sarache, W. (2021). A three-objective stochastic location-inventory-routing model for agricultural waste-based biofuel supply chain. Computers \& Industrial Engineering, 162, 107759. https://doi.org/doi.org/10.1016/j.cie.2021.107759; Morales-Chavez, M. M., Sarache, W., & Costa, Y. (2018). Towards a comprehensive model of a biofuel supply chain optimization from coffee crop residues. Transportation Research Part E: Logistics and Transportation Review, 116(May), 136–162. https://doi.org/10.1016/j.tre.2018.06.001; Morales-Chavez, M. M., Sarache, W., Costa, Y., & Soto, J. (2020). Multiobjective stochastic scheduling of upstream operations in a sustainable sugarcane supply chain. Journal of Cleaner Production, 123305. https://doi.org/10.1016/j.jclepro.2020.123305; Moreno-Camacho, C. A., Montoya-Torres, J. R., Jaegler, A., & Gondran, N. (2019). Sustainability metrics for real case applications of the supply chain network design problem: A systematic literature review. Journal of Cleaner Production, 231, 600–618. https://doi.org/10.1016/j.jclepro.2019.05.278; Mottaghi, M., Bairamzadeh, S., & M.S., P. (2022). A taxonomic review and analysis on biomass supply chain design and planning: New trends, methodologies and applications. Industrial Crops and Products, 180. https://doi.org/10.1016/j.indcrop.2022.114747; Nakhjirkan, S., Rafiei, F. M., & Kashan, A. H. (2019). Developing an integrated decision making model in supply chain under demand uncertainty using genetic algorithm and network data envelopment analysis. International Journal of Mathematics in Operational Research, 14(1), 53 – 81. https://doi.org/10.1504/IJMOR.2019.096979; Nasr, N., Niaki, S. T. A., Hussenzadek Kashan, A., & Seifbarghy, M. (2021). An efficient solution method for an agri-fresh food supply chain: hybridization of Lagrangian relaxation and genetic algorithm. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-021-13718-8; Nematollahi, M., & Tajbakhsh, A. (2020). Past, present, and prospective themes of sustainable agricultural supply chains: A content analysis. Journal of Cleaner Production, 271. https://doi.org/10.1016/j.jclepro.2020.122201; Ng, R. T. L., & Maravelias, C. T. (2016). Design of Cellulosic Ethanol Supply Chains with Regional Depots. Industrial and Engineering Chemistry Research, 55(12). https://doi.org/10.1021/acs.iecr.5b03677; Nguyen, T. H., Granger, J., Pandya, D., & Paustian, K. (2019). High-resolution multi-objective optimization of feedstock landscape design for hybrid first and second generation biorefineries. Applied Energy, 238, 1484–1496. https://doi.org/10.1016/j.apenergy.2019.01.117; O’Neill, E. G., & Maravelias, C. T. (2021). Towards integrated landscape design and biofuel supply chain optimization. Current Opinion in Chemical Engineering, 31, 1–7. https://doi.org/10.1016/j.coche.2020.100666; OCDE, & FAO, F. and A. O. of U. N.-. (2017). Perspectivas Agrícolas OCDE-FAO. https://doi.org/10.1007/BF02915673; ONU. (2018). Generación de residuos. https://www.unep.org/es/noticias-y-reportajes/comunicado-de-prensa/un-tercio-de-los-residuos-de-america-latina-y-el-caribe; Organizacion de las naciones Unidas - Medio Ambiente (ONU). (2018). Perspectiva de la Gestión de Residuos en América Latina y el Caribe Perspectiva de la Gestión de Residuos en América Latina y el Caribe.; Pehlivan, C., Augusto, V., & Xie, X. (2014). Dynamic capacity planning and location of hierarchical service networks under service level constraints. IEEE Transactions on Automation Science and Engineering, 11(3), 863–880. https://doi.org/10.1109/TASE.2014.2309255; Pourhejazy, P., Kwon, O. K., & Lim, H. (2019). Integrating Sustainability into the Optimization of Fuel Logistics Networks. KSCE Journal of Civil Engineering, 23(3), 1369 – 1383. https://doi.org/10.1007/s12205-019-1373-7; Programa Mundial de Alimentos. (2020). Programa Mundial de Alimentos. https://www.un.org/sustainabledevelopment/es/hunger/; Rabbani, M., Amirhossein Sadati, S., & Farrokhi-Asl, H. (2020). Incorporating location routing model and decision making techniques in industrial waste management: Application in the automotive industry. Computers and Industrial Engineering, 148. https://doi.org/10.1016/j.cie.2020.106692; Rabbani, M., Heidari, R., & Yazdanparast, R. (2019). A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation. European Journal of Operational Research, 272(3), 945 – 961. https://doi.org/10.1016/j.ejor.2018.07.024; Rahbari, M., Arshadi Khamseh, A., Sadati-Keneti, Y., & Jafari, M. J. (2022). A risk-based green location-inventory-routing problem for hazardous materials: NSGA II, MOSA, and multi-objective black widow optimization. Environment, Development and Sustainability, 24(2), 2804 – 2840. https://doi.org/10.1007/s10668-021-01555-1; Ríos, P. (2018). Metodología de la Investigación: Un enfoque pedagógico. Editorial Cognitus CA.; Rocha, M. V. P., de Matos, L. J. B. L., Lima, L. P. D., Figueiredo, P. M. D. S., Lucena, I. L., Fernandes, F. A. N., & Gonçalves, L. R. B. (2014). Ultrasound-assisted production of biodiesel and ethanol from spent coffee grounds. Bioresource Technology, 167, 343–348. https://doi.org/10.1016/j.biortech.2014.06.032; Rodríguez Valencia, N., Zambrano Franco, A., Rodríguez, N., & Zambrano, D. (2010). Los subproductos del café: fuente de energía renovable. In Avances Técnicos Cenicafé (Colombia)(no. 393) 0120-0178 (Issue 3). https://doi.org/doi.org/ISSN-0120-0178; Romero, C. (1993). Teoría de la decisión multicriterio: conceptos, técnicas y aplicaciones. (Issue 338 ROM).; Romero, C., & Rehman, T. (2003). Multiple criteria analysis for agricultural decisions (Vol. 11). Elsevier.; Saif-Eddine, A. S., El-Beheiry, M. M., & El-Kharbotly, A. K. (2019). An improved genetic algorithm for optimizing total supply chain cost in inventory location routing problem. Ain Shams Engineering Journal, 10(1), 63–76. https://doi.org/10.1016/j.asej.2018.09.002; Sampieri, R., Fernández, C., & Baptista, P. (2010). METODOLOGÍA de la investigación (5th ed.). Mc Graw Hill.; Sarache, W., & Morales-Chavez, M. M. (2016). Localización, transporte e inventarios: tres decisiones estructurales en el diseño de cadenas de abastecimiento (Editorial Universidad Nacional de Colombia (ed.)).; Sarma, D., Das, A., & Bera, U. K. (2020). Uncertain demand estimation with optimization of time and cost using Facebook disaster map in emergency relief operation. Applied Soft Computing, 87, 105992. https://doi.org/10.1016/j.asoc.2019.105992; Sasikumar, P., & Kannan, G. (2008a). Issues in reverse supply chains, part I: End-of-life product recovery and inventory management - an overview. International Journal of Sustainable Engineering, 1(3), 154–172. https://doi.org/10.1080/19397030802433860; Sasikumar, P., & Kannan, G. (2008b). Issues in reverse supply chains, part II: Reverse distribution issues - an overview. International Journal of Sustainable Engineering, 1(4), 234–249. https://doi.org/10.1080/19397030802509974; Schaffel, S. B., & La Rovere, E. L. (2010). The quest for eco-social efficiency in biofuels production in Brazil. Journal of Cleaner Production, 18(16–17), 1663–1670. https://doi.org/10.1016/j.jclepro.2010.06.031; Serageldin, I., & Steer, A. (1994). Making development sustainable: from concepts to action. In Making development sustainable: from concepts to action. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041151110&partnerID=40&md5=e7bb7fe34d6c61fd78bf0acf58238f88; Seuring, S, & Gold, S. (2012). Conducting content-analysis based literature reviews in supply chain management. Supply Chain Management, 17(5), 544–555. https://doi.org/10.1108/13598541211258609; Seuring, Stefan, & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699–1710. https://doi.org/10.1016/j.jclepro.2008.04.020; Shanmugam, S., Hari, A., Kumar, D., Rajendran, K., Mathimani, T., Atabani, A. E., Brindhadevi, K., & Pugazhendhi, A. (2021). Recent developments and strategies in genome engineering and integrated fermentation approaches for biobutanol production from microalgae. Fuel, 285. https://doi.org/10.1016/j.fuel.2020.119052; Sharma, B., Ingalls, R. G., Jones, C. L., & Khanchi, A. (2013). Biomass supply chain design and analysis: Basis, overview, modeling, challenges, and future. Renewable and Sustainable Energy Reviews, 24(0), 608–627. https://doi.org/http://dx.doi.org/10.1016/j.rser.2013.03.049; Singh, A. R., Mishra, P. K., Jain, R., & Khurana, M. K. (2012). Design of global supply chain network with operational risks. International Journal of Advanced Manufacturing Technology, 60(1–4), 273–290. https://doi.org/10.1007/s00170-011-3615-9; Tavakkoli-Moghaddam, R., & Raziei, Z. (2016). A New Bi-Objective Location-Routing-Inventory Problem with Fuzzy Demands. IFAC-PapersOnLine, 49(12), 1116–1121. https://doi.org/10.1016/J.IFACOL.2016.07.646; Tavana, M., Abtahi, A.-R., Di Caprio, D., Hashemi, R., & Yousefi-Zenouz, R. (2018). An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences, 64, 21 – 37. https://doi.org/10.1016/j.seps.2017.12.004; Tavana, M., Tohidi, H., Alimohammadi, M., & Lesansalmasi, R. (2021). A location-inventory-routing model for green supply chains with low-carbon emissions under uncertainty. Environmental Science and Pollution Research, 28(36), 50636 – 50648. https://doi.org/10.1007/s11356-021-13815-8; Triana, C. F., Quintero, J. A., Agudelo, R. A., Cardona, C. A., & Higuita, J. C. (2011). Analysis of coffee cut-stems (CCS) as raw material for fuel ethanol production. Energy, 36(7), 4182–4190. https://doi.org/10.1016/j.energy.2011.04.025; Valderrama, C. V., Santiba\vnez-González, E., Pimentel, B., Candia-Véjar, A., & Canales-Bustos, L. (2020). Designing an environmental supply chain network in the mining industry to reduce carbon emissions. Journal of Cleaner Production, 119688.; Van Engeland, J., Beliën, J., De Boeck, L., & De Jaeger, S. (2020). Literature review: Strategic network optimization models in waste reverse supply chains. Omega (United Kingdom), 91. https://doi.org/10.1016/j.omega.2018.12.001; Waltho, C., Elhedhli, S., & Gzara, F. (2019). Green supply chain network design: A review focused on policy adoption and emission quantification. International Journal of Production Economics, 208, 305–318. https://doi.org/10.1016/j.ijpe.2018.12.003; Williams, P. R. D., Inman, D., Aden, A., & Heath, G. A. (2009). Environmental and sustainability factors associated with next-generation biofuels in the U.S.: What do we really know? Environmental Science and Technology, 43(13), 4763–4775. https://doi.org/10.1021/es900250d; Wu, W., Zhou, W., Lin, Y., Xie, Y., & Jin, W. (2021). A hybrid metaheuristic algorithm for location inventory routing problem with time windows and fuel consumption. Expert Systems with Applications, 166. https://doi.org/10.1016/j.eswa.2020.114034; Yaghoubi, A., & Akrami, F. (2019). Proposing a new model for location - routing problem of perishable raw material suppliers with using meta-heuristic algorithms. Heliyon, 5(12), e03020. https://doi.org/10.1016/j.heliyon.2019.e03020; Yao, X., & Askin, R. (2019). Review of supply chain configuration and design decision-making for new product. International Journal of Production Research, 57(7), 2226–2246. https://doi.org/10.1080/00207543.2019.1567954; Yuchi, Q., Wang, N., He, Z., & Chen, H. (2021). Hybrid heuristic for the location-inventory-routing problem in closed-loop supply chain. International Transactions in Operational Research, 28(3), 1265 – 1295. https://doi.org/10.1111/itor.12621; Zandkarimkhani, S., Mina, H., Biuki, M., & Govindan, K. (2020). A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design. Annals of Operations Research, 295(1), 425 – 452. https://doi.org/10.1007/s10479-020-03677-7; Zeleny, M. (1973). Compromise programming, multiple criteria decision-making. Multiple Criteria Decision Making. University of South Carolina Press, Columbia, 263–301.; Zhalechian, M., Tavakkoli-Moghaddam, R., Zahiri, B., & Mohammadi, M. (2016). Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review, 89, 182–214. https://doi.org/10.1016/j.tre.2016.02.011; Zhang, Y., Qi, M., Miao, L., & Liu, E. (2014). Hybrid metaheuristic solutions to inventory location routing problem. Transportation Research Part E: Logistics and Transportation Review, 70(1), 305–323. https://doi.org/10.1016/j.tre.2014.07.010; Zhao, J., & Ke, G. Y. (2017). Incorporating inventory risks in location-routing models for explosive waste management. International Journal of Production Economics, 193, 123–136. https://doi.org/10.1016/j.ijpe.2017.07.001; Zhao, X., Ke, Y., Zuo, J., Xiong, W., & Wu, P. (2020). Evaluation of sustainable transport research in 2000 e 2019. Journal of Cleaner Production, 256, 120404. https://doi.org/10.1016/j.jclepro.2020.120404; Zheng, X., Yin, M., & Zhang, Y. (2019). Integrated optimization of location, inventory and routing in supply chain network design. Transportation Research Part B: Methodological, 121, 1–20. https://doi.org/10.1016/j.trb.2019.01.003; https://repositorio.unal.edu.co/handle/unal/84077; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/