A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems

Detalhes bibliográficos
Autor(a) principal: G. Wiman
Data de Publicação: 2011
Outros Autores: Gustavo Schweickardt, Vladimiro Miranda
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/2373
Resumo: Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.
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spelling A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systemsMetaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.2017-11-16T13:35:01Z2011-01-01T00:00:00Z2011info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/2373engG. WimanGustavo SchweickardtVladimiro Mirandainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:08Zoai:repositorio.inesctec.pt:123456789/2373Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:42.694593Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
title A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
spellingShingle A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
G. Wiman
title_short A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
title_full A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
title_fullStr A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
title_full_unstemmed A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
title_sort A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems
author G. Wiman
author_facet G. Wiman
Gustavo Schweickardt
Vladimiro Miranda
author_role author
author2 Gustavo Schweickardt
Vladimiro Miranda
author2_role author
author
dc.contributor.author.fl_str_mv G. Wiman
Gustavo Schweickardt
Vladimiro Miranda
description Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01T00:00:00Z
2011
2017-11-16T13:35:01Z
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/2373
url http://repositorio.inesctec.pt/handle/123456789/2373
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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