Parallel strategies for a multi-criteria GRASP algorithm

Detalhes bibliográficos
Autor(a) principal: Vianna,Dalessandro Soares
Data de Publicação: 2007
Outros Autores: Arroyo,José Elias Claudio, Vieira,Pedro Sampaio, Azeredo,Thiago Ribeiro de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Production
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132007000100006
Resumo: This paper proposes different strategies of parallelizing a multi-criteria GRASP (Greedy Randomized Adaptive Search Problem) algorithm. The parallel GRASP algorithm is applied to the multi-criteria minimum spanning tree problem, which is NP-hard. In this problem, a vector of costs is defined for each edge of the graph and the goal is to find all the efficient or Pareto optimal spanning trees (Pareto-optimal solutions). Each process finds a subset of efficient solutions. These subsets are joined using different strategies to obtain the final set of efficient solutions. The multi-criteria GRASP algorithm with the different parallel strategies are tested on complete graphs with n = 20, 30 and 50 nodes and r = 2 and 3 criteria. The computational results show that the proposed parallel algorithms reduce the execution time and the results obtained by the sequential version were improved.
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spelling Parallel strategies for a multi-criteria GRASP algorithmParallel GRASP algorithmmulti-criteria combinatorial optimizationminimum spanning treeThis paper proposes different strategies of parallelizing a multi-criteria GRASP (Greedy Randomized Adaptive Search Problem) algorithm. The parallel GRASP algorithm is applied to the multi-criteria minimum spanning tree problem, which is NP-hard. In this problem, a vector of costs is defined for each edge of the graph and the goal is to find all the efficient or Pareto optimal spanning trees (Pareto-optimal solutions). Each process finds a subset of efficient solutions. These subsets are joined using different strategies to obtain the final set of efficient solutions. The multi-criteria GRASP algorithm with the different parallel strategies are tested on complete graphs with n = 20, 30 and 50 nodes and r = 2 and 3 criteria. The computational results show that the proposed parallel algorithms reduce the execution time and the results obtained by the sequential version were improved.Associação Brasileira de Engenharia de Produção2007-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132007000100006Production v.17 n.1 2007reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/S0103-65132007000100006info:eu-repo/semantics/openAccessVianna,Dalessandro SoaresArroyo,José Elias ClaudioVieira,Pedro SampaioAzeredo,Thiago Ribeiro deeng2007-08-23T00:00:00Zoai:scielo:S0103-65132007000100006Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2007-08-23T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv Parallel strategies for a multi-criteria GRASP algorithm
title Parallel strategies for a multi-criteria GRASP algorithm
spellingShingle Parallel strategies for a multi-criteria GRASP algorithm
Vianna,Dalessandro Soares
Parallel GRASP algorithm
multi-criteria combinatorial optimization
minimum spanning tree
title_short Parallel strategies for a multi-criteria GRASP algorithm
title_full Parallel strategies for a multi-criteria GRASP algorithm
title_fullStr Parallel strategies for a multi-criteria GRASP algorithm
title_full_unstemmed Parallel strategies for a multi-criteria GRASP algorithm
title_sort Parallel strategies for a multi-criteria GRASP algorithm
author Vianna,Dalessandro Soares
author_facet Vianna,Dalessandro Soares
Arroyo,José Elias Claudio
Vieira,Pedro Sampaio
Azeredo,Thiago Ribeiro de
author_role author
author2 Arroyo,José Elias Claudio
Vieira,Pedro Sampaio
Azeredo,Thiago Ribeiro de
author2_role author
author
author
dc.contributor.author.fl_str_mv Vianna,Dalessandro Soares
Arroyo,José Elias Claudio
Vieira,Pedro Sampaio
Azeredo,Thiago Ribeiro de
dc.subject.por.fl_str_mv Parallel GRASP algorithm
multi-criteria combinatorial optimization
minimum spanning tree
topic Parallel GRASP algorithm
multi-criteria combinatorial optimization
minimum spanning tree
description This paper proposes different strategies of parallelizing a multi-criteria GRASP (Greedy Randomized Adaptive Search Problem) algorithm. The parallel GRASP algorithm is applied to the multi-criteria minimum spanning tree problem, which is NP-hard. In this problem, a vector of costs is defined for each edge of the graph and the goal is to find all the efficient or Pareto optimal spanning trees (Pareto-optimal solutions). Each process finds a subset of efficient solutions. These subsets are joined using different strategies to obtain the final set of efficient solutions. The multi-criteria GRASP algorithm with the different parallel strategies are tested on complete graphs with n = 20, 30 and 50 nodes and r = 2 and 3 criteria. The computational results show that the proposed parallel algorithms reduce the execution time and the results obtained by the sequential version were improved.
publishDate 2007
dc.date.none.fl_str_mv 2007-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132007000100006
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132007000100006
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0103-65132007000100006
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
dc.source.none.fl_str_mv Production v.17 n.1 2007
reponame:Production
instname:Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron:ABEPRO
instname_str Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron_str ABEPRO
institution ABEPRO
reponame_str Production
collection Production
repository.name.fl_str_mv Production - Associação Brasileira de Engenharia de Produção (ABEPRO)
repository.mail.fl_str_mv ||production@editoracubo.com.br
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