Suchergebnisse - "Population-based algorithms"

Leveraging social networks as an optimization approach

Autoren: Ghadirian, Hamed Seyed Jalaleddin, Mousavirad

Quelle: Intelligent Systems with Applications. 26

Schlagwörter: Consensus-based optimization, Evolutionary algorithm, Image thresholding, Optimization, Population-based algorithms, Social network

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-54206
https://doi.org/10.1016/j.iswa.2025.200506

L0-Norm based Image Pansharpening by using population-based algorithms

Autoren: Günen, M. Akif Pérez Delgado, María Luisa Beşdok, Erkan

Quelle: GREDOS. Repositorio Institucional de la Universidad de Salamanca
Universidad de Salamanca (USAL)
AIMS Mathematics, Vol 9, Iss 11, Pp 32578-32628 (2024)

Schlagwörter: Population-based algorithms, Colony Search Algorithm, population-based algorithms, QA1-939, colony search algorithm, pansharpening, Pansharpening, image fusion, Mathematics

Zugangs-URL: http://hdl.handle.net/10366/161428
https://doaj.org/article/5046061347d948faa2ae3e890102d4ca
https://hdl.handle.net/10366/161428

L0-Norm based Image Pansharpening by using population-based algorithms

Autoren: Mehmet Akif Günen María-Luisa Pérez-Delgado Erkan Beşdok

Quelle: AIMS Mathematics, Vol 9, Iss 11, Pp 32578-32628 (2024)

Schlagwörter: pansharpening, image fusion, population-based algorithms, colony search algorithm, Mathematics, QA1-939

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2473-6988

Zugangs-URL: https://doaj.org/article/5046061347d948faa2ae3e890102d4ca

A New Approach to Detecting and Preventing Populations Stagnation Through Dynamic Changes in Multi-Population-Based Algorithms

Autoren: Krystian Łapa Danuta Rutkowska Aleksander Byrski et al.

Quelle: Journal of Artificial Intelligence and Soft Computing Research. 13:289-306

Schlagwörter: migration topologies, multi-population-based algorithms, population stagnation, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11573/1692302
https://doi.org/10.2478/jaiscr-2023-0020

Memetic-Based Biogeography Optimization Model for the Optimal Design of Mechanical Systems

Autoren: Arcílio Carlos Ferreira Peixoto Carlos A. Conceição António

Quelle: Mathematics ; Volume 13 ; Issue 3 ; Pages: 492

Schlagwörter: memetic algorithms, biogeography-based optimization, multi-objective optimization, population-based algorithms

Dateibeschreibung: application/pdf

Relation: E2: Control Theory and Mechanics; https://dx.doi.org/10.3390/math13030492

Verfügbarkeit: https://doi.org/10.3390/math13030492

L0-Norm based Image Pansharpening by using population-based algorithms

Autoren: G?nen, M. Akif P?rez Delgado, Mar?a Luisa Be?dok, Erkan

Schlagwörter: Population-based algorithms, Colony Search Algorithm, Pansharpening, image fusion

Zugangs-URL: https://hdl.handle.net/10366/161428

A Novel Center of Mass Optimization (CMO) Algorithm for Truss Design Problems

Autoren: Hesam Varaee

Quelle: Journal of Soft Computing in Civil Engineering, Vol 8, Iss 2, Pp 119-142 (2024)

Schlagwörter: center of mass, population-based algorithms, mathematical and engineering optimization problems, wilcoxon rank-sum test, anova test, Technology

Dateibeschreibung: electronic resource

Relation: https://www.jsoftcivil.com/article_196429_a71ca3885615fd9930c2b5a0f83dbf3f.pdf; https://doaj.org/toc/2588-2872

Zugangs-URL: https://doaj.org/article/c83b24ab85d147c5a7f738e5c22e2f63

A survey on dynamic populations in bio-inspired algorithms

Autoren: Farinati, Davide Vanneschi, Leonardo NOVA Information Management School (NOVA IMS) et al.

Weitere Verfasser: Farinati, Davide Vanneschi, Leonardo NOVA Information Management School (NOVA IMS) et al.

Schlagwörter: Population-based algorithms, Bio-inspired algorithms, Population size, Dynamic population, Adaptive population, Software, Theoretical Computer Science, Hardware and Architecture, Computer Science Applications

Dateibeschreibung: application/pdf

Relation: 1389-2576; PURE: 96124299

Verfügbarkeit: http://hdl.handle.net/10362/170138

Already Moderate Population Sizes Provably Yield Strong Robustness to Noise

Autoren: Antipov, Denis Doerr, Benjamin Ivanova, Alexandra et al.

Weitere Verfasser: Antipov, Denis Doerr, Benjamin Ivanova, Alexandra et al.

Quelle: GECCO '24: Genetic and Evolutionary Computation Conference ; https://hal.science/hal-04649104 ; GECCO '24: Genetic and Evolutionary Computation Conference, 2024, Melbourne VIC, Australia. pp.1524-1532, ⟨10.1145/3638529.3654196⟩

Schlagwörter: Evolutionary algorithms, Random search heuristics Noisy optimization Runtime analysis Theory Population-based algorithms, Random search heuristics Noisy optimization, Runtime analysis, Theory, Population-based algorithms, [INFO]Computer Science [cs]

Geographisches Schlagwort: Melbourne VIC, Australia

Verfügbarkeit: https://hal.science/hal-04649104
https://hal.science/hal-04649104v1/document
https://hal.science/hal-04649104v1/file/Antipov_Doerr_Ivanova__Already_Moderate_Populations_Sizes_Yield_Robustness_to_Noise__GECCO__2024.pdf
https://doi.org/10.1145/3638529.3654196

Multi-Objective Population-based Optimization Algorithms for Scheduling of Manufacturing Entities

Autoren: Petrović, Milica Jokić, Aleksandar Miljković, Zoran et al.

Quelle: Proceedings of the 26th International Conference on Methods and Models in Automation and Robotics (MMAR 2022)

Schlagwörter: Multi-objective optimization, 0209 industrial biotechnology, Population-based algorithms, Manufacturing resources scheduling, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Zugangs-URL: https://machinery.mas.bg.ac.rs/handle/123456789/3968

Generalized Net Model of Coyote Optimization Algorithm

Autoren: Olympia Roeva Dafina Zoteva Peter Vassilev

Quelle: International Journal Bioautomation, Vol 26, Iss 4, Pp 353-360 (2022)

Schlagwörter: coyote optimization algorithm, QH301-705.5, population-based algorithms, generalized net, metaheuristic, Biology (General)

Zugangs-URL: https://doaj.org/article/208d33cf02564ff39904dd4ba4ed4b46

Multi-objective simulation optimization for complex urban mass rapid transit systems

Autoren: David Schmaranzer Roland Braune Karl F. Doerner

Quelle: Annals of Operations Research. 305:449-486

Schlagwörter: Population-based algorithms, HEADWAY, Transit network frequencies setting problem, DEMAND, Multi-directional local search, 0211 other engineering and technologies, Public transportation, GENETIC ALGORITHM, BWL, 02 engineering and technology, MR, FREQUENCY, TIME, MODEL, Multi-objective optimization, NETWORK DESIGN, 502052 Betriebswirtschaftslehre, Simulation optimization, 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, 502052 Business administration, ADAPTATION, Headway optimization

Dateibeschreibung: application/pdf

Zugangs-URL: https://link.springer.com/content/pdf/10.1007/s10479-019-03378-w.pdf
https://ucrisportal.univie.ac.at/de/publications/bfaa31bc-5771-48dc-981b-6872546df517
https://doi.org/10.1007/s10479-019-03378-w
https://ideas.repec.org/a/spr/annopr/v305y2021i1d10.1007_s10479-019-03378-w.html
https://link.springer.com/content/pdf/10.1007%2Fs10479-019-03378-w.pdf
https://link.springer.com/article/10.1007/s10479-019-03378-w
https://dblp.uni-trier.de/db/journals/anor/anor305.html#SchmaranzerBD21
https://doi.org/10.1007/s10479-019-03378-w

On the benefits of populations for the exploitation speed of standard steady-state genetic algorithms

Autoren: Dogan Corus Pietro S. Oliveto

Quelle: Proceedings of the Genetic and Evolutionary Computation Conference. :1452-1460

Schlagwörter: FOS: Computer and information sciences, crossover, Evolutionary algorithms, genetic algorithms (computational aspects), 13. Climate action, population-based algorithms, Computer Science - Neural and Evolutionary Computing, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), recombination, genetic algorithms, runtime analysis

Dateibeschreibung: application/xml; application/pdf

Zugangs-URL: http://eprints.whiterose.ac.uk/144388/1/1903.10976v1.pdf
https://link.springer.com/content/pdf/10.1007/s00453-020-00743-1.pdf
http://arxiv.org/abs/1903.10976
https://zbmath.org/7272777
https://doi.org/10.1007/s00453-020-00743-1
http://arxiv.org/pdf/1903.10976.pdf
https://arxiv.org/abs/1903.10976
https://dblp.uni-trier.de/db/conf/gecco/gecco2019.html#CorusO19
https://eprints.whiterose.ac.uk/164018/
http://dblp.uni-trier.de/db/journals/corr/corr1903.html#abs-1903-10976
https://dl.acm.org/doi/pdf/10.1145/3321707.3321783
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica82.html#CorusO20
https://link.springer.com/article/10.1007/s00453-020-00743-1
https://link.springer.com/content/pdf/10.1007/s00453-020-00743-1.pdf

Comparison of population-based algorithms for optimizing thinnings and rotation using a process-based growth model

Autoren: Hailian Xue Annikki Mäkelä Lauri Valsta et al.

Weitere Verfasser: Hailian Xue Annikki Mäkelä Lauri Valsta et al.

Quelle: Scandinavian Journal of Forest Research. 34:458-468

Schlagwörter: 0106 biological sciences, PRODUCTIVITY, population-based algorithms, Algorithm performance, SIMPLEX-METHOD, Forestry, CARBON-BALANCE, 04 agricultural and veterinary sciences, 15. Life on land, 01 natural sciences, PINE, optimal thinning, STAND MANAGEMENT, SEARCH, 0401 agriculture, forestry, and fisheries, process-based model, OPTIMIZATION, Environmental Sciences

Dateibeschreibung: application/pdf

Zugangs-URL: https://helda.helsinki.fi/bitstream/10138/310435/1/Xue_et_al_2019_preprint.pdf
https://helda.helsinki.fi/handle/10138/310435
https://helda.helsinki.fi/bitstream/10138/310435/1/Xue_et_al_2019_preprint.pdf
https://www.tandfonline.com/doi/full/10.1080/02827581.2019.1581252
https://researchportal.helsinki.fi/en/publications/comparison-of-population-based-algorithms-for-optimizing-thinning
http://hdl.handle.net/10138/310435

A new optimization algorithm based on mimicking the voting process for leader selection

Autoren: Pavel Trojovský Mohammad Dehghani

Quelle: PeerJ Computer Science, Vol 8, p e976 (2022)

Schlagwörter: Optimization, Optimization problem, Human-based metahurestic algorithm, Stochastic algorithms, Population-based algorithms, Applied mathematics, Electronic computers. Computer science, QA75.5-76.95

Dateibeschreibung: electronic resource

Relation: https://peerj.com/articles/cs-976.pdf; https://peerj.com/articles/cs-976/; https://doaj.org/toc/2376-5992

Zugangs-URL: https://doaj.org/article/bde9e829c78b4403b2d3855c2e91e94c

Classification of Program Texts Represented as Markov Chains with Biology-Inspired Algorithms-Enhanced Extreme Learning Machines

Autoren: Liliya A. Demidova Artyom V. Gorchakov

Quelle: Algorithms, Vol 15, Iss 329, p 329 (2022)

Schlagwörter: program text classification, Markov chains, extreme learning machines, population-based algorithms, biology-inspired algorithms, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, QA75.5-76.95

Relation: https://www.mdpi.com/1999-4893/15/9/329; https://doaj.org/toc/1999-4893; https://doaj.org/article/1a5976a4ce744f89a0d8117937ba78f0

Verfügbarkeit: https://doi.org/10.3390/a15090329
https://doaj.org/article/1a5976a4ce744f89a0d8117937ba78f0

Differential Evolution with Reversible Linear Transformations

Autoren: Tomczak, Jakub M. Wȩglarz-Tomczak, Ewelina Eiben, Agoston E.

Quelle: Tomczak, J M, Wȩglarz-Tomczak, E & Eiben, A E 2020, Differential Evolution with Reversible Linear Transformations. in GECCO '20 : Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, pp. 205-206, 2020 Genetic and Evolutionary Computation Conference, GECCO 2020, Cancun, Mexico, 8/07/20. https://doi.org/10.1145/3377929.3389972

Schlagwörter: Black-box optimization, Population-based algorithms, Reversible computation

Dateibeschreibung: application/pdf

Relation: info:eu-repo/semantics/altIdentifier/hdl/https://hdl.handle.net/1871.1/25656031-fb10-452c-bf97-cd6432bdad4d; info:eu-repo/semantics/altIdentifier/isbn/9781450371278; urn:ISBN:9781450371278

Verfügbarkeit: https://research.vu.nl/en/publications/25656031-fb10-452c-bf97-cd6432bdad4d
https://doi.org/10.1145/3377929.3389972
https://hdl.handle.net/1871.1/25656031-fb10-452c-bf97-cd6432bdad4d
https://research.vu.nl/ws/files/130179584/Differential_Evolution_with_Reversible_Linear_Transformations.pdf
https://www.scopus.com/pages/publications/85089728474
https://www.scopus.com/inward/citedby.url?scp=85089728474&partnerID=8YFLogxK

Comparison of population-based algorithms for optimizing thinnings and rotation using a process-based growth model

Autoren: Xue, Hailian Mäkelä, Aino Annikki Valsta, Lauri Tapani et al.

Weitere Verfasser: Xue, Hailian Mäkelä, Aino Annikki Valsta, Lauri Tapani et al.

Schlagwörter: Forestry, Algorithm performance, optimal thinning, population-based algorithms, process-based model, CARBON-BALANCE, STAND MANAGEMENT, SIMPLEX-METHOD, OPTIMIZATION, PRODUCTIVITY, SEARCH, PINE

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/10138/310435; 000480619900006

Verfügbarkeit: http://hdl.handle.net/10138/310435

Larger Offspring Populations Help the (1 + (λ, λ)) Genetic Algorithm to Overcome the Noise

Autoren: Ivanova, A. Antipov, D. Doerr, B. et al.

Weitere Verfasser: Ivanova, A. Antipov, D. Doerr, B. et al.

Quelle: http://dx.doi.org/10.1145/3583131.3590514.

Schlagwörter: Evolutionary Computation, Noisy Optimization, Population-based Algorithms

Relation: http://purl.org/au-research/grants/arc/DP190103894; Proceedings of the Genetic and Evolutionary Computation Conference (GECCO, 2023), 2023 / Paquete, L. (ed./s), pp.919-928; https://hdl.handle.net/2440/139331; Antipov, D. [0000-0001-7906-096X]

Verfügbarkeit: https://hdl.handle.net/2440/139331
https://doi.org/10.1145/3583131.3590514

A population-based automatic clustering algorithm for image segmentation

Autoren: Mousavirad, Seyed Schaefer, Gerald Helali Moghadam, Mahshid et al.

Quelle: GECCO 2021 Companion - Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion. :1931-1936

Schlagwörter: automatic clustering, human mental search, image segmentation, optimisation, population-based algorithms, Evolutionary algorithms, Optimization, Automatic clustering algorithm, Conventional algorithms, K-means, Local optima, Meta heuristic algorithm, Number of clusters, Optimisation problems, Population-based algorithm, K-means clustering

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-55664