Hybrid Particle Swarm Optimiser using multi-neighborhood topologies

Detalhes bibliográficos
Autor(a) principal: Hamdan, S. A.
Data de Publicação: 2008
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204
Resumo: Hybrid Particle Swarm Optimization (PSO) algorithm that combines the idea of global best model with the idea of local best model is presented in this paper. The hybrid PSO mixes the use of the traditional velocity and position update rules of star, ring and Von Neumann topologies all together. The objective of building PSO on multi-models is that, to find a better solution without trapping in local minimums models, and to achieve faster convergence rate. This paper describes how the hybrid model will get the benefit of the strength of gbest and lbest models. It investigates when it would be better for the particle to update its velocity using star or ring or Von Neumann topologies. The performance of proposed method is compared to other standard models of PSO using variant set of benchmark functions to investigate the improvement.
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spelling Hybrid Particle Swarm Optimiser using multi-neighborhood topologiesPSOhybrid PSOglobal bestlocal bestNeighborhood TopologiesStarRingVon Neu- mannHybrid Particle Swarm Optimization (PSO) algorithm that combines the idea of global best model with the idea of local best model is presented in this paper. The hybrid PSO mixes the use of the traditional velocity and position update rules of star, ring and Von Neumann topologies all together. The objective of building PSO on multi-models is that, to find a better solution without trapping in local minimums models, and to achieve faster convergence rate. This paper describes how the hybrid model will get the benefit of the strength of gbest and lbest models. It investigates when it would be better for the particle to update its velocity using star or ring or Von Neumann topologies. The performance of proposed method is compared to other standard models of PSO using variant set of benchmark functions to investigate the improvement.Editora da UFLA2008-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204INFOCOMP Journal of Computer Science; Vol. 7 No. 1 (2008): March, 2008; 36-431982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204/189Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessHamdan, S. A.2015-06-27T23:26:38Zoai:infocomp.dcc.ufla.br:article/204Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:24.236301INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
title Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
spellingShingle Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
Hamdan, S. A.
PSO
hybrid PSO
global best
local best
Neighborhood Topologies
Star
Ring
Von Neu- mann
title_short Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
title_full Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
title_fullStr Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
title_full_unstemmed Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
title_sort Hybrid Particle Swarm Optimiser using multi-neighborhood topologies
author Hamdan, S. A.
author_facet Hamdan, S. A.
author_role author
dc.contributor.author.fl_str_mv Hamdan, S. A.
dc.subject.por.fl_str_mv PSO
hybrid PSO
global best
local best
Neighborhood Topologies
Star
Ring
Von Neu- mann
topic PSO
hybrid PSO
global best
local best
Neighborhood Topologies
Star
Ring
Von Neu- mann
description Hybrid Particle Swarm Optimization (PSO) algorithm that combines the idea of global best model with the idea of local best model is presented in this paper. The hybrid PSO mixes the use of the traditional velocity and position update rules of star, ring and Von Neumann topologies all together. The objective of building PSO on multi-models is that, to find a better solution without trapping in local minimums models, and to achieve faster convergence rate. This paper describes how the hybrid model will get the benefit of the strength of gbest and lbest models. It investigates when it would be better for the particle to update its velocity using star or ring or Von Neumann topologies. The performance of proposed method is compared to other standard models of PSO using variant set of benchmark functions to investigate the improvement.
publishDate 2008
dc.date.none.fl_str_mv 2008-03-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/204/189
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 7 No. 1 (2008): March, 2008; 36-43
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
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