A Hybrid Heuristic Approach to Solve the Multi Level Capacitated Lot Sizing Problem

Detalhes bibliográficos
Autor(a) principal: Motta Toledo, Claudio Fabiano
Data de Publicação: 2011
Outros Autores: Ribeiro de Oliveira, Renato Resende, Franca, Paulo Morelato [UNESP], IEEE
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/194753
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.
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spelling A Hybrid Heuristic Approach to Solve the Multi Level Capacitated Lot Sizing ProblemGenetic algorithmsProduction planningLot sizingOptimizationHeuristic algorithmsThis 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.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Sao Paulo, Inst Math & Comp Sci, BR-05508 Sao Paulo, BrazilUniv Fed Lavras, Dept Comp Sci, Lavras, BrazilUniv Estadual Paulista, Dept Math Stat & Computat, Sao Paulo, BrazilUniv Estadual Paulista, Dept Math Stat & Computat, Sao Paulo, BrazilFAPESP: 2010/101330IeeeUniversidade de São Paulo (USP)Universidade Federal de Lavras (UFLA)Universidade Estadual Paulista (Unesp)Motta Toledo, Claudio FabianoRibeiro de Oliveira, Renato ResendeFranca, Paulo Morelato [UNESP]IEEE2020-12-10T16:36:33Z2020-12-10T16:36:33Z2011-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1194-12012011 Ieee Congress On Evolutionary Computation (cec). New York: Ieee, p. 1194-1201, 2011.http://hdl.handle.net/11449/194753WOS:000312932600162Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2011 Ieee Congress On Evolutionary Computation (cec)info:eu-repo/semantics/openAccess2021-10-22T20:36:08Zoai:repositorio.unesp.br:11449/194753Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:58:38.460312Repositório 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
Motta Toledo, Claudio Fabiano
Genetic algorithms
Production planning
Lot sizing
Optimization
Heuristic algorithms
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 Motta Toledo, Claudio Fabiano
author_facet Motta Toledo, Claudio Fabiano
Ribeiro de Oliveira, Renato Resende
Franca, Paulo Morelato [UNESP]
IEEE
author_role author
author2 Ribeiro de Oliveira, Renato Resende
Franca, Paulo Morelato [UNESP]
IEEE
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Federal de Lavras (UFLA)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Motta Toledo, Claudio Fabiano
Ribeiro de Oliveira, Renato Resende
Franca, Paulo Morelato [UNESP]
IEEE
dc.subject.por.fl_str_mv Genetic algorithms
Production planning
Lot sizing
Optimization
Heuristic algorithms
topic Genetic algorithms
Production planning
Lot sizing
Optimization
Heuristic algorithms
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.
publishDate 2011
dc.date.none.fl_str_mv 2011-01-01
2020-12-10T16:36:33Z
2020-12-10T16:36:33Z
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 2011 Ieee Congress On Evolutionary Computation (cec). New York: Ieee, p. 1194-1201, 2011.
http://hdl.handle.net/11449/194753
WOS:000312932600162
identifier_str_mv 2011 Ieee Congress On Evolutionary Computation (cec). New York: Ieee, p. 1194-1201, 2011.
WOS:000312932600162
url http://hdl.handle.net/11449/194753
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2011 Ieee Congress On Evolutionary Computation (cec)
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.publisher.none.fl_str_mv Ieee
publisher.none.fl_str_mv Ieee
dc.source.none.fl_str_mv Web of Science
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
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