Project scheduling under multiple resources constraints using a genetic algorithm

Detalhes bibliográficos
Autor(a) principal: Magalhães-Mendes, J.
Data de Publicação: 2008
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/4241
Resumo: The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.
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spelling Project scheduling under multiple resources constraints using a genetic algorithmConstruction managementProject managementSchedulingGenetic algorithmRCPSPThe resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.World Scientific and Engineering Academy and Society (WSEAS)Repositório Científico do Instituto Politécnico do PortoMagalhães-Mendes, J.2014-03-25T14:57:52Z20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/4241eng1109-952610400.22/4241info: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:RCAAP2023-03-13T12:44:18Zoai:recipp.ipp.pt:10400.22/4241Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:25:09.000976Repositório 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 Project scheduling under multiple resources constraints using a genetic algorithm
title Project scheduling under multiple resources constraints using a genetic algorithm
spellingShingle Project scheduling under multiple resources constraints using a genetic algorithm
Magalhães-Mendes, J.
Construction management
Project management
Scheduling
Genetic algorithm
RCPSP
title_short Project scheduling under multiple resources constraints using a genetic algorithm
title_full Project scheduling under multiple resources constraints using a genetic algorithm
title_fullStr Project scheduling under multiple resources constraints using a genetic algorithm
title_full_unstemmed Project scheduling under multiple resources constraints using a genetic algorithm
title_sort Project scheduling under multiple resources constraints using a genetic algorithm
author Magalhães-Mendes, J.
author_facet Magalhães-Mendes, J.
author_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Magalhães-Mendes, J.
dc.subject.por.fl_str_mv Construction management
Project management
Scheduling
Genetic algorithm
RCPSP
topic Construction management
Project management
Scheduling
Genetic algorithm
RCPSP
description The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.
publishDate 2008
dc.date.none.fl_str_mv 2008
2008-01-01T00:00:00Z
2014-03-25T14:57:52Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/4241
url http://hdl.handle.net/10400.22/4241
dc.language.iso.fl_str_mv eng
language eng
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10400.22/4241
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eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv World Scientific and Engineering Academy and Society (WSEAS)
publisher.none.fl_str_mv World Scientific and Engineering Academy and Society (WSEAS)
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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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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