Evaluation of a proposed optimization method for discrete-event simulation models
Autor(a) principal: | |
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Data de Publicação: | 2012 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa operacional (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300004 |
Resumo: | Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency. |
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Evaluation of a proposed optimization method for discrete-event simulation modelsmetaheuristicssimulation optimizationdiscrete-event simulationOptimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.Sociedade Brasileira de Pesquisa Operacional2012-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300004Pesquisa Operacional v.32 n.3 2012reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382012005000021info:eu-repo/semantics/openAccessPinho,Alexandre Ferreira deMontevechi,José Arnaldo BarraMarins,Fernando Augusto SilvaCosta,Rafael Florêncio da SilvaMiranda,Rafael de CarvalhoFriend,Jonathan Danieleng2012-12-10T00:00:00Zoai:scielo:S0101-74382012000300004Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2012-12-10T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false |
dc.title.none.fl_str_mv |
Evaluation of a proposed optimization method for discrete-event simulation models |
title |
Evaluation of a proposed optimization method for discrete-event simulation models |
spellingShingle |
Evaluation of a proposed optimization method for discrete-event simulation models Pinho,Alexandre Ferreira de metaheuristics simulation optimization discrete-event simulation |
title_short |
Evaluation of a proposed optimization method for discrete-event simulation models |
title_full |
Evaluation of a proposed optimization method for discrete-event simulation models |
title_fullStr |
Evaluation of a proposed optimization method for discrete-event simulation models |
title_full_unstemmed |
Evaluation of a proposed optimization method for discrete-event simulation models |
title_sort |
Evaluation of a proposed optimization method for discrete-event simulation models |
author |
Pinho,Alexandre Ferreira de |
author_facet |
Pinho,Alexandre Ferreira de Montevechi,José Arnaldo Barra Marins,Fernando Augusto Silva Costa,Rafael Florêncio da Silva Miranda,Rafael de Carvalho Friend,Jonathan Daniel |
author_role |
author |
author2 |
Montevechi,José Arnaldo Barra Marins,Fernando Augusto Silva Costa,Rafael Florêncio da Silva Miranda,Rafael de Carvalho Friend,Jonathan Daniel |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Pinho,Alexandre Ferreira de Montevechi,José Arnaldo Barra Marins,Fernando Augusto Silva Costa,Rafael Florêncio da Silva Miranda,Rafael de Carvalho Friend,Jonathan Daniel |
dc.subject.por.fl_str_mv |
metaheuristics simulation optimization discrete-event simulation |
topic |
metaheuristics simulation optimization discrete-event simulation |
description |
Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency. |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-12-01 |
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=S0101-74382012000300004 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382012000300004 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/S0101-74382012005000021 |
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.32 n.3 2012 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 |
_version_ |
1750318017420460032 |