A particle swarm optimizer for multi-objective optimization

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This paper proposes a hybrid particle swarm approach called Simple Multi-Objective Particle Swarm Optimizer (SMOPSO) which incorporates Pareto dominance, an elitist policy, and two techniques to maintain diversity: a mutation operator and a grid which is used as a geographical location over objectiv...

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Detalles Bibliográficos
Autores principales:	Cagnina, Leticia, Esquivel, Susana Cecilia
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2005
Materias:	Ciencias Informáticas Optimization particle swarm optimization multi-objective optimization Pareto optimality
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/22941
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-22941
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 Optimization particle swarm optimization multi-objective optimization Pareto optimality
spellingShingle	Ciencias Informáticas Optimization particle swarm optimization multi-objective optimization Pareto optimality Cagnina, Leticia Esquivel, Susana Cecilia A particle swarm optimizer for multi-objective optimization
topic_facet	Ciencias Informáticas Optimization particle swarm optimization multi-objective optimization Pareto optimality
description	This paper proposes a hybrid particle swarm approach called Simple Multi-Objective Particle Swarm Optimizer (SMOPSO) which incorporates Pareto dominance, an elitist policy, and two techniques to maintain diversity: a mutation operator and a grid which is used as a geographical location over objective function space. In order to validate our approach we use three well-known test functions proposed in the specialized literature. Preliminary simulations results are presented and compared with those obtained with the Pareto Archived Evolution Strategy (PAES) and the Multi-Objective Genetic Algorithm 2 (MOGA2). These results also show that the SMOPSO algorithm is a promising alternative to tackle multi-objective optimization problems.
format	Objeto de conferencia Objeto de conferencia
author	Cagnina, Leticia Esquivel, Susana Cecilia
author_facet	Cagnina, Leticia Esquivel, Susana Cecilia
author_sort	Cagnina, Leticia
title	A particle swarm optimizer for multi-objective optimization
title_short	A particle swarm optimizer for multi-objective optimization
title_full	A particle swarm optimizer for multi-objective optimization
title_fullStr	A particle swarm optimizer for multi-objective optimization
title_full_unstemmed	A particle swarm optimizer for multi-objective optimization
title_sort	particle swarm optimizer for multi-objective optimization
publishDate	2005
url	http://sedici.unlp.edu.ar/handle/10915/22941
work_keys_str_mv	AT cagninaleticia aparticleswarmoptimizerformultiobjectiveoptimization AT esquivelsusanacecilia aparticleswarmoptimizerformultiobjectiveoptimization AT cagninaleticia particleswarmoptimizerformultiobjectiveoptimization AT esquivelsusanacecilia particleswarmoptimizerformultiobjectiveoptimization
bdutipo_str	Repositorios
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A particle swarm optimizer for multi-objective optimization

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