Solving Hard Multiobjective Problems with a Hybridized Method

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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 point...

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Autores principales: Cagnina, Leticia, Esquivel, Susana Cecilia
Formato: Articulo
Lenguaje:Inglés
Publicado: 2010
Materias:
Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9678
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-2.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9678
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
spellingShingle Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
Cagnina, Leticia
Esquivel, Susana Cecilia
Solving Hard Multiobjective Problems with a Hybridized Method
topic_facet Ciencias Informáticas
optimización multiobjetivo
métodos de restricción
optimización de enjambre de particulas
particle swarm optimization
multi-objective optimization
epsilon-constraint method
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.
format Articulo
Articulo
author Cagnina, Leticia
Esquivel, Susana Cecilia
author_facet Cagnina, Leticia
Esquivel, Susana Cecilia
author_sort Cagnina, Leticia
title Solving Hard Multiobjective Problems with a Hybridized 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
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/9678
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-2.pdf
work_keys_str_mv AT cagninaleticia solvinghardmultiobjectiveproblemswithahybridizedmethod
AT esquivelsusanacecilia solvinghardmultiobjectiveproblemswithahybridizedmethod
bdutipo_str Repositorios
_version_ 1764820492443713538

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