Solving Hard Multiobjective Problems with a Hybridized Method

Autores
Cagnina, Leticia; Esquivel, Susana Cecilia
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will be generated and then, new intermediate points will be calculated using an interpolation method, to increase the among of points in the output Pareto front. The proposed approach is validated using two difficult multiobjective test problems and the results are compared with those obtained by a multiobjective evolutionary algorithm representative of the state of the art: NSGA-II.
Facultad de Informática
Materia
Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9678
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/9678
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Solving Hard Multiobjective Problems with a Hybridized MethodCagnina, LeticiaEsquivel, Susana CeciliaCiencias Informáticasoptimización multiobjetivométodos de restricciónoptimización de enjambre de particulasparticle swarm optimizationmulti-objective optimizationepsilon-constraint methodThis paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will be generated and then, new intermediate points will be calculated using an interpolation method, to increase the among of points in the output Pareto front. The proposed approach is validated using two difficult multiobjective test problems and the results are compared with those obtained by a multiobjective evolutionary algorithm representative of the state of the art: NSGA-II.Facultad de Informática2010-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf117-122http://sedici.unlp.edu.ar/handle/10915/9678enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-2.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:32:22Zoai:sedici.unlp.edu.ar:10915/9678Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:32:22.425SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Solving Hard Multiobjective Problems with a Hybridized Method
title Solving Hard Multiobjective Problems with a Hybridized Method
spellingShingle Solving Hard Multiobjective Problems with a Hybridized Method
Cagnina, Leticia
Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
title_short Solving Hard Multiobjective Problems with a Hybridized Method
title_full Solving Hard Multiobjective Problems with a Hybridized Method
title_fullStr Solving Hard Multiobjective Problems with a Hybridized Method
title_full_unstemmed Solving Hard Multiobjective Problems with a Hybridized Method
title_sort Solving Hard Multiobjective Problems with a Hybridized Method
dc.creator.none.fl_str_mv Cagnina, Leticia
Esquivel, Susana Cecilia
author Cagnina, Leticia
author_facet Cagnina, Leticia
Esquivel, Susana Cecilia
author_role author
author2 Esquivel, Susana Cecilia
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
topic Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
dc.description.none.fl_txt_mv This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will be generated and then, new intermediate points will be calculated using an interpolation method, to increase the among of points in the output Pareto front. The proposed approach is validated using two difficult multiobjective test problems and the results are compared with those obtained by a multiobjective evolutionary algorithm representative of the state of the art: NSGA-II.
Facultad de Informática
description This paper presents a hybrid method to solve hard multiobjective problems. The proposed approach adopts an epsilon-constraint method which uses a Particle Swarm Optimizer to get points near of the true Pareto front. In this approach, only few points will be generated and then, new intermediate points will be calculated using an interpolation method, to increase the among of points in the output Pareto front. The proposed approach is validated using two difficult multiobjective test problems and the results are compared with those obtained by a multiobjective evolutionary algorithm representative of the state of the art: NSGA-II.
publishDate 2010
dc.date.none.fl_str_mv 2010-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/9678
url http://sedici.unlp.edu.ar/handle/10915/9678
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-2.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
117-122
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 12.982451

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