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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/9486
Ver los metadatos del registro completo
id |
CONICETDig_97304a629ecebfe4234c302134a9f106 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/9486 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
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 |
_version_ |
1846082613926690816 |
score |
13.22299 |