A hybrid heuristic approach to solve the multi level capacitated lot sizing problem

Detalhes bibliográficos
Autor(a) principal: Toledo, Claudio Fabiano Motta
Data de Publicação: 2011
Outros Autores: De Oliveira, Renato Resende Ribeiro, Franca, Paulo Morelato [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/CEC.2011.5949752
http://hdl.handle.net/11449/219699
Resumo: This paper presents preliminary results found by a hybrid heuristic applied to solve the Multi-Level Capacitated Lot Sizing Problem (MLCLSP). The proposed method combines a multi-population genetic algorithm and fix-and-optimize heuristic. These methods are also integrated to a mathematical programming approach. For this, a mathematical reformulation of MLCLSP model is proposed to embed the exact solution of the model in the heuristic approaches. The hybrid heuristic is evaluated in two sets of benchmark instances. The solutions found are compared with those reached by other methods from literature. The preliminary results obtained indicate that the hybrid heuristic outperforms other approaches in the majority of problems solved. © 2011 IEEE.
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spelling A hybrid heuristic approach to solve the multi level capacitated lot sizing problemGenetic algorithmsHeuristic algorithmsLot sizingOptimizationProduction planningThis paper presents preliminary results found by a hybrid heuristic applied to solve the Multi-Level Capacitated Lot Sizing Problem (MLCLSP). The proposed method combines a multi-population genetic algorithm and fix-and-optimize heuristic. These methods are also integrated to a mathematical programming approach. For this, a mathematical reformulation of MLCLSP model is proposed to embed the exact solution of the model in the heuristic approaches. The hybrid heuristic is evaluated in two sets of benchmark instances. The solutions found are compared with those reached by other methods from literature. The preliminary results obtained indicate that the hybrid heuristic outperforms other approaches in the majority of problems solved. © 2011 IEEE.University of São Paulo Institute of Mathematics and Computer ScienceFederal University of Lavras Dept. of Computer ScienceUNESP - Dept. of Mathematics Statistics and ComputationUNESP - Dept. of Mathematics Statistics and ComputationUniversidade de São Paulo (USP)Dept. of Computer ScienceUniversidade Estadual Paulista (UNESP)Toledo, Claudio Fabiano MottaDe Oliveira, Renato Resende RibeiroFranca, Paulo Morelato [UNESP]2022-04-28T18:57:07Z2022-04-28T18:57:07Z2011-08-29info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1194-1201http://dx.doi.org/10.1109/CEC.2011.59497522011 IEEE Congress of Evolutionary Computation, CEC 2011, p. 1194-1201.http://hdl.handle.net/11449/21969910.1109/CEC.2011.59497522-s2.0-80051965398Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2011 IEEE Congress of Evolutionary Computation, CEC 2011info:eu-repo/semantics/openAccess2022-04-28T18:57:07Zoai:repositorio.unesp.br:11449/219699Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:34:38.088167Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
title A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
spellingShingle A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
Toledo, Claudio Fabiano Motta
Genetic algorithms
Heuristic algorithms
Lot sizing
Optimization
Production planning
title_short A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
title_full A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
title_fullStr A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
title_full_unstemmed A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
title_sort A hybrid heuristic approach to solve the multi level capacitated lot sizing problem
author Toledo, Claudio Fabiano Motta
author_facet Toledo, Claudio Fabiano Motta
De Oliveira, Renato Resende Ribeiro
Franca, Paulo Morelato [UNESP]
author_role author
author2 De Oliveira, Renato Resende Ribeiro
Franca, Paulo Morelato [UNESP]
author2_role author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Dept. of Computer Science
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Toledo, Claudio Fabiano Motta
De Oliveira, Renato Resende Ribeiro
Franca, Paulo Morelato [UNESP]
dc.subject.por.fl_str_mv Genetic algorithms
Heuristic algorithms
Lot sizing
Optimization
Production planning
topic Genetic algorithms
Heuristic algorithms
Lot sizing
Optimization
Production planning
description This paper presents preliminary results found by a hybrid heuristic applied to solve the Multi-Level Capacitated Lot Sizing Problem (MLCLSP). The proposed method combines a multi-population genetic algorithm and fix-and-optimize heuristic. These methods are also integrated to a mathematical programming approach. For this, a mathematical reformulation of MLCLSP model is proposed to embed the exact solution of the model in the heuristic approaches. The hybrid heuristic is evaluated in two sets of benchmark instances. The solutions found are compared with those reached by other methods from literature. The preliminary results obtained indicate that the hybrid heuristic outperforms other approaches in the majority of problems solved. © 2011 IEEE.
publishDate 2011
dc.date.none.fl_str_mv 2011-08-29
2022-04-28T18:57:07Z
2022-04-28T18:57:07Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/CEC.2011.5949752
2011 IEEE Congress of Evolutionary Computation, CEC 2011, p. 1194-1201.
http://hdl.handle.net/11449/219699
10.1109/CEC.2011.5949752
2-s2.0-80051965398
url http://dx.doi.org/10.1109/CEC.2011.5949752
http://hdl.handle.net/11449/219699
identifier_str_mv 2011 IEEE Congress of Evolutionary Computation, CEC 2011, p. 1194-1201.
10.1109/CEC.2011.5949752
2-s2.0-80051965398
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2011 IEEE Congress of Evolutionary Computation, CEC 2011
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1194-1201
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129337741803520

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