Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation

Detalhes bibliográficos
Autor(a) principal: Lins,Isis Didier
Data de Publicação: 2009
Outros Autores: Droguett,Enrique López
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100003
Resumo: This paper attempts to provide a more realistic approach to the characterization of system reliability when handling redundancy allocation problems: it considers repairable series-parallel systems comprised of components subjected to corrective maintenance actions with failure-repair cycles modeled by renewal processes. A multiobjective optimization approach is applied since increasing the number of redundancies not only enlarges system reliability but also its associated costs. Then a multiobjective genetic algorithm is coupled with discrete event simulation and its solutions present the compromise between system reliability and cost. Two examples are provided. In the first one, the proposed algorithm is validated by comparison with results obtained from a system devised as to allow for analytical solutions of the objective functions. The second case analyzes a repairable system subjected to perfect repairs. Results from both examples show that the proposed method can be a valuable tool for the decision maker when choosing the system design.
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spelling Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulationavailabilityredundancy allocationmultiobjective optimization in system designThis paper attempts to provide a more realistic approach to the characterization of system reliability when handling redundancy allocation problems: it considers repairable series-parallel systems comprised of components subjected to corrective maintenance actions with failure-repair cycles modeled by renewal processes. A multiobjective optimization approach is applied since increasing the number of redundancies not only enlarges system reliability but also its associated costs. Then a multiobjective genetic algorithm is coupled with discrete event simulation and its solutions present the compromise between system reliability and cost. Two examples are provided. In the first one, the proposed algorithm is validated by comparison with results obtained from a system devised as to allow for analytical solutions of the objective functions. The second case analyzes a repairable system subjected to perfect repairs. Results from both examples show that the proposed method can be a valuable tool for the decision maker when choosing the system design.Sociedade Brasileira de Pesquisa Operacional2009-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100003Pesquisa Operacional v.29 n.1 2009reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382009000100003info:eu-repo/semantics/openAccessLins,Isis DidierDroguett,Enrique Lópezeng2009-05-28T00:00:00Zoai:scielo:S0101-74382009000100003Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2009-05-28T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
title Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
spellingShingle Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
Lins,Isis Didier
availability
redundancy allocation
multiobjective optimization in system design
title_short Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
title_full Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
title_fullStr Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
title_full_unstemmed Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
title_sort Multiobjective optimization of availability and cost in repairable systems design via genetic algorithms and discrete event simulation
author Lins,Isis Didier
author_facet Lins,Isis Didier
Droguett,Enrique López
author_role author
author2 Droguett,Enrique López
author2_role author
dc.contributor.author.fl_str_mv Lins,Isis Didier
Droguett,Enrique López
dc.subject.por.fl_str_mv availability
redundancy allocation
multiobjective optimization in system design
topic availability
redundancy allocation
multiobjective optimization in system design
description This paper attempts to provide a more realistic approach to the characterization of system reliability when handling redundancy allocation problems: it considers repairable series-parallel systems comprised of components subjected to corrective maintenance actions with failure-repair cycles modeled by renewal processes. A multiobjective optimization approach is applied since increasing the number of redundancies not only enlarges system reliability but also its associated costs. Then a multiobjective genetic algorithm is coupled with discrete event simulation and its solutions present the compromise between system reliability and cost. Two examples are provided. In the first one, the proposed algorithm is validated by comparison with results obtained from a system devised as to allow for analytical solutions of the objective functions. The second case analyzes a repairable system subjected to perfect repairs. Results from both examples show that the proposed method can be a valuable tool for the decision maker when choosing the system design.
publishDate 2009
dc.date.none.fl_str_mv 2009-04-01
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=S0101-74382009000100003
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100003
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-74382009000100003
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 Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.29 n.1 2009
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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