A decision support model for handling customer orders in business chain
One of the elements of the modern trade and services market is a business chain solution (chain store/retail chain). An example of a business chain is, e.g., a restaurant chain, where each restaurant in the chain has the same decor, organization, menu, and delivery method. Although such solutions ha...
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| Published in: | Neurocomputing (Amsterdam) Vol. 482; pp. 298 - 309 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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14.04.2022
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| ISSN: | 0925-2312, 1872-8286 |
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| Abstract | One of the elements of the modern trade and services market is a business chain solution (chain store/retail chain). An example of a business chain is, e.g., a restaurant chain, where each restaurant in the chain has the same decor, organization, menu, and delivery method. Although such solutions have been known for decades, the rapid development of IT technology, the widespread access to the Internet as well as the development of mobile technologies have changed and modernized their formula. Many customers place orders remotely with the option of delivery to their door. This method of ordering and fulfilling orders is becoming more and more popular and ever more common in the recent period due to the pandemic and the resulting restrictions and limitations on the functioning of trade and services. The following key questions arise in relation to customer order processing for chain business managers: How to allocate individual customer orders to selected branches so that the cost of their processing (production and delivery) is the lowest?, How to deliver on time?, etc. To answer these questions, a decision support model has been developed, which combines routing, allocation and planning problems for restaurant/store chains. Two ways to implement the model have been proposed. The first one uses the methods of mathematical modeling and programming, and the other, which is a proprietary approach that integrates the mechanisms of evolution (specialized representations, repair mechanisms, genetic operators, etc.), uses constraint logic programming and dedicated heuristics. In addition, procedures for constraint handling and presolving have been developed. |
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| AbstractList | One of the elements of the modern trade and services market is a business chain solution (chain store/retail chain). An example of a business chain is, e.g., a restaurant chain, where each restaurant in the chain has the same decor, organization, menu, and delivery method. Although such solutions have been known for decades, the rapid development of IT technology, the widespread access to the Internet as well as the development of mobile technologies have changed and modernized their formula. Many customers place orders remotely with the option of delivery to their door. This method of ordering and fulfilling orders is becoming more and more popular and ever more common in the recent period due to the pandemic and the resulting restrictions and limitations on the functioning of trade and services. The following key questions arise in relation to customer order processing for chain business managers: How to allocate individual customer orders to selected branches so that the cost of their processing (production and delivery) is the lowest?, How to deliver on time?, etc. To answer these questions, a decision support model has been developed, which combines routing, allocation and planning problems for restaurant/store chains. Two ways to implement the model have been proposed. The first one uses the methods of mathematical modeling and programming, and the other, which is a proprietary approach that integrates the mechanisms of evolution (specialized representations, repair mechanisms, genetic operators, etc.), uses constraint logic programming and dedicated heuristics. In addition, procedures for constraint handling and presolving have been developed. |
| Author | Bocewicz, Grzegorz Nielsen, Izabela Wikarek, Jarosław Sitek, Paweł |
| Author_xml | – sequence: 1 givenname: Paweł orcidid: 0000-0001-6108-0241 surname: Sitek fullname: Sitek, Paweł email: sitek@tu.kielce.pl organization: Department of Control and Management Systems, Kielce University of Technology, Poland – sequence: 2 givenname: Jarosław surname: Wikarek fullname: Wikarek, Jarosław email: j.wikarek@tu.kielce.pl organization: Department of Control and Management Systems, Kielce University of Technology, Poland – sequence: 3 givenname: Grzegorz surname: Bocewicz fullname: Bocewicz, Grzegorz email: bocewicz@ie.tu.koszalin.pl organization: Faculty of Electronics and Computer Science, Koszalin University of Technology, Poland – sequence: 4 givenname: Izabela surname: Nielsen fullname: Nielsen, Izabela email: izabela@mp.aau.dk organization: Department of Materials and Production, Aalborg University, Denmark |
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| Keywords | Hybrid approach Constraint logic programming Business chain Dedicated genetic algorithm Constraint handling procedure Decision support Mathematical programming |
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| References | Mula, Peidro, Díaz-Madroñero, Vicens (b0015) 2010; 204 Rossi, Van Beek, Walsh (b0110) 2006 Sahay, Ierapetritou (b0020) 2013; 59 P. Sitek, J. Wikarek, A hybrid programming framework for modeling and solving constraint satisfaction and optimization problems, Sci. Programm., 2016 (2016), Article ID 5102616, 13 pages, DOI: https://doi.org/10.1155/2016/5102616. CPLEX Optimizer Euchi, Sadok (b0090) 2021; 44 Wassan, Wassan, Nagy, Salhi (b0050) 2017; 78 C. Archetti, M.G. Speranza, A survey on matheuristics for routing problems, EURO J. Comput. Optim., 2(223), 2014, DOI:10.1007/s13675-014-0030-7. Pang (b0075) 2011; 38 Kumar, Panneerselvam (b0040) 2012; 4 W. Hwang, R. Enkhbat, A. Bayarbaatar, Methods and algorithms for solving the resource allocation problem, Int. J. Pure Appl. Math. – IJPAM, 54(3) (2009). Gendreau, Guertin, Potvin, Séguin (b0080) 2006; 14 N. Katoh, A. Shioura, T. Ibaraki, Resource allocation problems, in: Pardalos P., Du DZ., Graham R. (eds) Handbook of Combinatorial Optimization. Springer, 2013, New York, NY, DOI: https://doi.org/10.1007/978-1-4419-7997-1_44. Gurobi M.N. Janardhanan, P. Nielsen, Q. Tang. Artificial bee colony algorithms for two-sided assembly line worker assignment and balancing problem, in: Omatu S., Rodríguez S., Villarrubia G., Faria P., Sitek P., Prieto J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol. 620, 2018, Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_2. J. Wikarek, P. Sitek, Optimization of customer order processing for the pizza chains, in: Rodríguez González S. et al. (eds) Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242, 2020, Springer, Cham, DOI: https://doi.org/10.1007/978-3-030-53829-3_3. Ropke, Cordeau, Vigo, Iori (b0060) 2007 Toth, Vigo (b0085) 2014 Kłosowski, Gola, Thibbotuwawa (b0130) 2018; 51 Karkory, Ali (b0125) 2013; 7 R. Jairo, T. Montoya, J.L Francob, S.N. Isazac, H.F. Jiménezd, N. Herazo-Padillae, A literature review on the vehicle routing problem with multiple depots, Comput. Ind. Eng., 79(2015) 115–129. Accessed June 06 2021. Gutiérrez-Jarpa, Desaulniers, Laporte, Marianov (b0065) 2010; 206 Koopman (b0025) 1957; 5 E. McArthur, S. Weaven, D. Rajiv, The evolution of retailing: A meta review of the literature, J. Macromarket., 36(3) (2016) DOI: https://doi.org/10.1177/0276146715602529. Eiben, Smith (b0120) 2015 Salhi, Wassan, Hajarat (b0055) 2013; 56 XPRESS solver-engine 10.1016/j.neucom.2021.06.099_b0045 10.1016/j.neucom.2021.06.099_b0100 10.1016/j.neucom.2021.06.099_b0105 10.1016/j.neucom.2021.06.099_b0005 Euchi (10.1016/j.neucom.2021.06.099_b0090) 2021; 44 Toth (10.1016/j.neucom.2021.06.099_b0085) 2014 Eiben (10.1016/j.neucom.2021.06.099_b0120) 2015 Pang (10.1016/j.neucom.2021.06.099_b0075) 2011; 38 Gendreau (10.1016/j.neucom.2021.06.099_b0080) 2006; 14 Koopman (10.1016/j.neucom.2021.06.099_b0025) 1957; 5 Karkory (10.1016/j.neucom.2021.06.099_b0125) 2013; 7 10.1016/j.neucom.2021.06.099_b0035 Ropke (10.1016/j.neucom.2021.06.099_b0060) 2007 Sahay (10.1016/j.neucom.2021.06.099_b0020) 2013; 59 10.1016/j.neucom.2021.06.099_b0010 Rossi (10.1016/j.neucom.2021.06.099_b0110) 2006 10.1016/j.neucom.2021.06.099_b0115 10.1016/j.neucom.2021.06.099_b0135 Gutiérrez-Jarpa (10.1016/j.neucom.2021.06.099_b0065) 2010; 206 Kłosowski (10.1016/j.neucom.2021.06.099_b0130) 2018; 51 Wassan (10.1016/j.neucom.2021.06.099_b0050) 2017; 78 Kumar (10.1016/j.neucom.2021.06.099_b0040) 2012; 4 Salhi (10.1016/j.neucom.2021.06.099_b0055) 2013; 56 10.1016/j.neucom.2021.06.099_b0070 10.1016/j.neucom.2021.06.099_b0030 Mula (10.1016/j.neucom.2021.06.099_b0015) 2010; 204 10.1016/j.neucom.2021.06.099_b0095 |
| References_xml | – reference: N. Katoh, A. Shioura, T. Ibaraki, Resource allocation problems, in: Pardalos P., Du DZ., Graham R. (eds) Handbook of Combinatorial Optimization. Springer, 2013, New York, NY, DOI: https://doi.org/10.1007/978-1-4419-7997-1_44. – volume: 5 start-page: 613 year: 1957 end-page: 626 ident: b0025 article-title: The theory of search, III: The optimum distribution of effort publication-title: Oper. Res. – volume: 206 start-page: 341 year: 2010 end-page: 349 ident: b0065 article-title: A branch-and-price algorithm for vehicle routing problem with deliveries, selective pickups and time windows publication-title: Eur. J. Oper. Res. – reference: P. Sitek, J. Wikarek, A hybrid programming framework for modeling and solving constraint satisfaction and optimization problems, Sci. Programm., 2016 (2016), Article ID 5102616, 13 pages, DOI: https://doi.org/10.1155/2016/5102616. – reference: XPRESS solver-engine, – volume: 44 start-page: 101236 year: 2021 ident: b0090 article-title: Hybrid genetic-sweep algorithm to solve the vehicle routing problem with drones publication-title: Phys. Commun. – reference: , Accessed June 06 2021. – year: 2007 ident: b0060 article-title: Branch-and-cut-and-price for the capacitated vehicle routing problem with two-dimensional constraints publication-title: Proceedings of ROUTE, Jekyll Island – reference: CPLEX Optimizer, – volume: 56 start-page: 22 year: 2013 end-page: 35 ident: b0055 article-title: The fleet size and mix vehicle routing problem with backhauls: formulation and set partitioning-based heuristics publication-title: Transp. Res. Part E: Log. Transp. Rev. – reference: W. Hwang, R. Enkhbat, A. Bayarbaatar, Methods and algorithms for solving the resource allocation problem, Int. J. Pure Appl. Math. – IJPAM, 54(3) (2009). – reference: M.N. Janardhanan, P. Nielsen, Q. Tang. Artificial bee colony algorithms for two-sided assembly line worker assignment and balancing problem, in: Omatu S., Rodríguez S., Villarrubia G., Faria P., Sitek P., Prieto J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol. 620, 2018, Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_2. – year: 2015 ident: b0120 article-title: Introduction to Evolutionary Computing – year: 2006 ident: b0110 article-title: Handbook of Constraint Programming (Foundations of Artificial Intelligence) – reference: R. Jairo, T. Montoya, J.L Francob, S.N. Isazac, H.F. Jiménezd, N. Herazo-Padillae, A literature review on the vehicle routing problem with multiple depots, Comput. Ind. Eng., 79(2015) 115–129. – volume: 14 start-page: 157 year: 2006 end-page: 174 ident: b0080 article-title: Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries publication-title: Transp. Res. Part E: Logistics Transp. – year: 2014 ident: b0085 article-title: Vehicle routing: problems, methods, and applications – volume: 4 start-page: 66 year: 2012 end-page: 74 ident: b0040 article-title: A survey on the vehicle routing problem and its variants publication-title: Intell. Inf. Manage. – volume: 204 start-page: 377 year: 2010 end-page: 390 ident: b0015 article-title: Mathematical programming models for supply chain production and transport planning publication-title: Eur. J. Oper. Res. – volume: 38 start-page: 11939 year: 2011 end-page: 11946 ident: b0075 article-title: An adaptive parallel route construction heuristic for the vehicle routing problem with time windows constraints publication-title: Expert Syst. Appl. – volume: 78 start-page: 454 year: 2017 end-page: 467 ident: b0050 article-title: The multiple trip vehicle routing problem with backhauls: formulation and a two-level variable neighbourhood search publication-title: Comput. Oper. Res. – reference: C. Archetti, M.G. Speranza, A survey on matheuristics for routing problems, EURO J. Comput. Optim., 2(223), 2014, DOI:10.1007/s13675-014-0030-7. – volume: 7 start-page: 1524 year: 2013 end-page: 1534 ident: b0125 article-title: Implementation of heuristics for solving travelling salesman problem using nearest neighbour and minimum spanning tree algorithms publication-title: World Acad. Sci. Eng. Technol. Int. J. Math. Comput. Phys. Electr. Comput. Eng. – reference: E. McArthur, S. Weaven, D. Rajiv, The evolution of retailing: A meta review of the literature, J. Macromarket., 36(3) (2016) DOI: https://doi.org/10.1177/0276146715602529. – reference: Gurobi, – reference: J. Wikarek, P. Sitek, Optimization of customer order processing for the pizza chains, in: Rodríguez González S. et al. (eds) Distributed Computing and Artificial Intelligence, Special Sessions, 17th International Conference. DCAI 2020. Advances in Intelligent Systems and Computing, vol 1242, 2020, Springer, Cham, DOI: https://doi.org/10.1007/978-3-030-53829-3_3. – volume: 59 start-page: 4612 year: 2013 end-page: 4626 ident: b0020 article-title: Supply chain management using an optimization driven simulation approach publication-title: AIChE J. – volume: 51 start-page: 1421 year: 2018 end-page: 1427 ident: b0130 article-title: Computational intelligence in control of AGV multimodal systems publication-title: IFAC-Papers Line – ident: 10.1016/j.neucom.2021.06.099_b0115 doi: 10.1155/2016/5102616 – ident: 10.1016/j.neucom.2021.06.099_b0045 doi: 10.1016/j.cie.2014.10.029 – year: 2007 ident: 10.1016/j.neucom.2021.06.099_b0060 article-title: Branch-and-cut-and-price for the capacitated vehicle routing problem with two-dimensional constraints publication-title: Proceedings of ROUTE, Jekyll Island – volume: 51 start-page: 1421 issue: 11 year: 2018 ident: 10.1016/j.neucom.2021.06.099_b0130 article-title: Computational intelligence in control of AGV multimodal systems publication-title: IFAC-Papers Line doi: 10.1016/j.ifacol.2018.08.315 – volume: 14 start-page: 157 issue: 3 year: 2006 ident: 10.1016/j.neucom.2021.06.099_b0080 article-title: Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries publication-title: Transp. Res. Part E: Logistics Transp. doi: 10.1016/j.trc.2006.03.002 – volume: 206 start-page: 341 issue: 12 year: 2010 ident: 10.1016/j.neucom.2021.06.099_b0065 article-title: A branch-and-price algorithm for vehicle routing problem with deliveries, selective pickups and time windows publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2010.02.037 – ident: 10.1016/j.neucom.2021.06.099_b0030 doi: 10.1007/978-1-4419-7997-1_44 – volume: 44 start-page: 101236 year: 2021 ident: 10.1016/j.neucom.2021.06.099_b0090 article-title: Hybrid genetic-sweep algorithm to solve the vehicle routing problem with drones publication-title: Phys. Commun. doi: 10.1016/j.phycom.2020.101236 – year: 2006 ident: 10.1016/j.neucom.2021.06.099_b0110 – ident: 10.1016/j.neucom.2021.06.099_b0095 – ident: 10.1016/j.neucom.2021.06.099_b0105 – ident: 10.1016/j.neucom.2021.06.099_b0005 doi: 10.1177/0276146715602529 – year: 2014 ident: 10.1016/j.neucom.2021.06.099_b0085 – ident: 10.1016/j.neucom.2021.06.099_b0010 doi: 10.1007/978-3-030-53829-3_3 – year: 2015 ident: 10.1016/j.neucom.2021.06.099_b0120 – volume: 204 start-page: 377 issue: 3 year: 2010 ident: 10.1016/j.neucom.2021.06.099_b0015 article-title: Mathematical programming models for supply chain production and transport planning publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2009.09.008 – volume: 78 start-page: 454 year: 2017 ident: 10.1016/j.neucom.2021.06.099_b0050 article-title: The multiple trip vehicle routing problem with backhauls: formulation and a two-level variable neighbourhood search publication-title: Comput. Oper. Res. doi: 10.1016/j.cor.2015.12.017 – volume: 7 start-page: 1524 year: 2013 ident: 10.1016/j.neucom.2021.06.099_b0125 article-title: Implementation of heuristics for solving travelling salesman problem using nearest neighbour and minimum spanning tree algorithms publication-title: World Acad. Sci. Eng. Technol. Int. J. Math. Comput. Phys. Electr. Comput. Eng. – volume: 59 start-page: 4612 year: 2013 ident: 10.1016/j.neucom.2021.06.099_b0020 article-title: Supply chain management using an optimization driven simulation approach publication-title: AIChE J. doi: 10.1002/aic.14226 – volume: 5 start-page: 613 year: 1957 ident: 10.1016/j.neucom.2021.06.099_b0025 article-title: The theory of search, III: The optimum distribution of effort publication-title: Oper. Res. doi: 10.1287/opre.5.5.613 – volume: 56 start-page: 22 year: 2013 ident: 10.1016/j.neucom.2021.06.099_b0055 article-title: The fleet size and mix vehicle routing problem with backhauls: formulation and set partitioning-based heuristics publication-title: Transp. Res. Part E: Log. Transp. Rev. doi: 10.1016/j.tre.2013.05.005 – ident: 10.1016/j.neucom.2021.06.099_b0135 doi: 10.1007/978-3-319-62410-5_2 – ident: 10.1016/j.neucom.2021.06.099_b0100 – ident: 10.1016/j.neucom.2021.06.099_b0070 doi: 10.1007/s13675-014-0030-7 – volume: 4 start-page: 66 issue: 03 year: 2012 ident: 10.1016/j.neucom.2021.06.099_b0040 article-title: A survey on the vehicle routing problem and its variants publication-title: Intell. Inf. Manage. – ident: 10.1016/j.neucom.2021.06.099_b0035 – volume: 38 start-page: 11939 issue: 9 year: 2011 ident: 10.1016/j.neucom.2021.06.099_b0075 article-title: An adaptive parallel route construction heuristic for the vehicle routing problem with time windows constraints publication-title: Expert Syst. Appl. doi: 10.1016/j.eswa.2011.03.088 |
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