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

Autores
Schweickardt, Gustavo Alejandro; Miranda, V.; Wiman, G.
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Schweickardt, Gustavo Alejandro. Fundacion Bariloche. Instituto de Economia Energetica; Argentina. Comision Nacional de Energia Atomica. Gerencia del Area de Investigaciones y Aplicaciones no Nucleares. Gerencia de Fisica (CAB); Argentina
Fil: Miranda, V.. Universidad de Porto; Portugal
Fil: Wiman, G.. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
Materia
Metaheuristic Algorithm
Swarm Intelligence
Fuzzy Sets
Electric Distribution
Phase Balancing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/9486

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spelling A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systemsSchweickardt, Gustavo AlejandroMiranda, V.Wiman, G.Metaheuristic AlgorithmSwarm IntelligenceFuzzy SetsElectric DistributionPhase Balancinghttps://purl.org/becyt/ford/5.2https://purl.org/becyt/ford/5Metaheuristics 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.Fil: Schweickardt, Gustavo Alejandro. Fundacion Bariloche. Instituto de Economia Energetica; Argentina. Comision Nacional de Energia Atomica. Gerencia del Area de Investigaciones y Aplicaciones no Nucleares. Gerencia de Fisica (CAB); ArgentinaFil: Miranda, V.. Universidad de Porto; PortugalFil: Wiman, G.. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; ArgentinaPlanta Piloto de Ingeniería Química2011-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/9486Schweickardt, Gustavo Alejandro; Miranda, V.; Wiman, G. ; A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems; Planta Piloto de Ingeniería Química; Latin American Applied Research; 41; 2; 6-2011; 113-1200327-07931851-8796enginfo:eu-repo/semantics/altIdentifier/url/http://www.laar.uns.edu.ar/indexes/i41_02.htminfo:eu-repo/semantics/altIdentifier/url/http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S0327-07932011000200003&lng=es&nrm=iso&tlng=eninfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:22:00Zoai:ri.conicet.gov.ar:11336/9486instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:22:00.526CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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
Schweickardt, Gustavo Alejandro
Metaheuristic Algorithm
Swarm Intelligence
Fuzzy Sets
Electric Distribution
Phase Balancing
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
dc.creator.none.fl_str_mv Schweickardt, Gustavo Alejandro
Miranda, V.
Wiman, G.
author Schweickardt, Gustavo Alejandro
author_facet Schweickardt, Gustavo Alejandro
Miranda, V.
Wiman, G.
author_role author
author2 Miranda, V.
Wiman, G.
author2_role author
author
dc.subject.none.fl_str_mv Metaheuristic Algorithm
Swarm Intelligence
Fuzzy Sets
Electric Distribution
Phase Balancing
topic Metaheuristic Algorithm
Swarm Intelligence
Fuzzy Sets
Electric Distribution
Phase Balancing
purl_subject.fl_str_mv https://purl.org/becyt/ford/5.2
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv 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.
Fil: Schweickardt, Gustavo Alejandro. Fundacion Bariloche. Instituto de Economia Energetica; Argentina. Comision Nacional de Energia Atomica. Gerencia del Area de Investigaciones y Aplicaciones no Nucleares. Gerencia de Fisica (CAB); Argentina
Fil: Miranda, V.. Universidad de Porto; Portugal
Fil: Wiman, G.. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina
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 2011-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/9486
Schweickardt, Gustavo Alejandro; Miranda, V.; Wiman, G. ; A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems; Planta Piloto de Ingeniería Química; Latin American Applied Research; 41; 2; 6-2011; 113-120
0327-0793
1851-8796
url http://hdl.handle.net/11336/9486
identifier_str_mv Schweickardt, Gustavo Alejandro; Miranda, V.; Wiman, G. ; A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems; Planta Piloto de Ingeniería Química; Latin American Applied Research; 41; 2; 6-2011; 113-120
0327-0793
1851-8796
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.laar.uns.edu.ar/indexes/i41_02.htm
info:eu-repo/semantics/altIdentifier/url/http://www.scielo.org.ar/scielo.php?script=sci_arttext&pid=S0327-07932011000200003&lng=es&nrm=iso&tlng=en
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Planta Piloto de Ingeniería Química
publisher.none.fl_str_mv Planta Piloto de Ingeniería Química
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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