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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9678
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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:UNLP2025-09-29T10:50:45Zoai: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:13292025-09-29 10:50:45.289SEDICI (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 |
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reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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score |
13.070432 |