A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem

Detalhes bibliográficos
Autor(a) principal: Gonçalves, José Fernando
Data de Publicação: 2005
Outros Autores: Mendes, J. J. M., Resende, Maurício G. C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/10058
Resumo: This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.
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spelling A Hybrid Genetic Algorithm for the Job Shop Scheduling ProblemJob ShopSchedulingGenetic AlgorithmHeuristicsRandom KeysThis paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.ElsevierRepositório Científico do Instituto Politécnico do PortoGonçalves, José FernandoMendes, J. J. M.Resende, Maurício G. C.2017-07-13T13:51:17Z20052005-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/10058eng10.1016/j.ejor.2004.03.012info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:51:29Zoai:recipp.ipp.pt:10400.22/10058Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:30:28.080204Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
title A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
spellingShingle A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
Gonçalves, José Fernando
Job Shop
Scheduling
Genetic Algorithm
Heuristics
Random Keys
title_short A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
title_full A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
title_fullStr A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
title_full_unstemmed A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
title_sort A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
author Gonçalves, José Fernando
author_facet Gonçalves, José Fernando
Mendes, J. J. M.
Resende, Maurício G. C.
author_role author
author2 Mendes, J. J. M.
Resende, Maurício G. C.
author2_role author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Gonçalves, José Fernando
Mendes, J. J. M.
Resende, Maurício G. C.
dc.subject.por.fl_str_mv Job Shop
Scheduling
Genetic Algorithm
Heuristics
Random Keys
topic Job Shop
Scheduling
Genetic Algorithm
Heuristics
Random Keys
description This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.
publishDate 2005
dc.date.none.fl_str_mv 2005
2005-01-01T00:00:00Z
2017-07-13T13:51:17Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/10058
url http://hdl.handle.net/10400.22/10058
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.ejor.2004.03.012
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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