Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging

Detalhes bibliográficos
Autor(a) principal: Toledo, Claudio F. M.
Data de Publicação: 2013
Outros Autores: Hossomi, Marcelo Y. B., Da Silva Arantes, Márcio, 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.2013.6557738
http://hdl.handle.net/11449/76310
Resumo: The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.
id UNSP_ff720eee15284db6de60b952950a3435
oai_identifier_str oai:repositorio.unesp.br:11449/76310
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogginggenetic algorithmhybrid metaheuristiclot-sizingmulti-levelCapacitated lot sizing problemComputational resultsHybrid Meta-heuristicLot sizingMixed-Integer ProgrammingBenchmarkingHeuristic methodsInteger programmingGenetic algorithmsThe present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.Institute of Mathematics and Computer Science University of São Paulo, São CarlosUNESP Dept. of Mathematics and ComputingUNESP Dept. of Mathematics and ComputingUniversidade de São Paulo (USP)Universidade Estadual Paulista (Unesp)Toledo, Claudio F. M.Hossomi, Marcelo Y. B.Da Silva Arantes, MárcioFranca, Paulo Morelato [UNESP]2014-05-27T11:30:11Z2014-05-27T11:30:11Z2013-08-21info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1483-1490http://dx.doi.org/10.1109/CEC.2013.65577382013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.http://hdl.handle.net/11449/7631010.1109/CEC.2013.65577382-s2.0-84881575854Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2013 IEEE Congress on Evolutionary Computation, CEC 2013info:eu-repo/semantics/openAccess2021-10-23T21:37:57Zoai:repositorio.unesp.br:11449/76310Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:57:37.533515Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
title Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
spellingShingle Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
Toledo, Claudio F. M.
genetic algorithm
hybrid metaheuristic
lot-sizing
multi-level
Capacitated lot sizing problem
Computational results
Hybrid Meta-heuristic
Lot sizing
Mixed-Integer Programming
Benchmarking
Heuristic methods
Integer programming
Genetic algorithms
title_short Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
title_full Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
title_fullStr Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
title_full_unstemmed Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
title_sort Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
author Toledo, Claudio F. M.
author_facet Toledo, Claudio F. M.
Hossomi, Marcelo Y. B.
Da Silva Arantes, Márcio
Franca, Paulo Morelato [UNESP]
author_role author
author2 Hossomi, Marcelo Y. B.
Da Silva Arantes, Márcio
Franca, Paulo Morelato [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Toledo, Claudio F. M.
Hossomi, Marcelo Y. B.
Da Silva Arantes, Márcio
Franca, Paulo Morelato [UNESP]
dc.subject.por.fl_str_mv genetic algorithm
hybrid metaheuristic
lot-sizing
multi-level
Capacitated lot sizing problem
Computational results
Hybrid Meta-heuristic
Lot sizing
Mixed-Integer Programming
Benchmarking
Heuristic methods
Integer programming
Genetic algorithms
topic genetic algorithm
hybrid metaheuristic
lot-sizing
multi-level
Capacitated lot sizing problem
Computational results
Hybrid Meta-heuristic
Lot sizing
Mixed-Integer Programming
Benchmarking
Heuristic methods
Integer programming
Genetic algorithms
description The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE.
publishDate 2013
dc.date.none.fl_str_mv 2013-08-21
2014-05-27T11:30:11Z
2014-05-27T11:30:11Z
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.2013.6557738
2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.
http://hdl.handle.net/11449/76310
10.1109/CEC.2013.6557738
2-s2.0-84881575854
url http://dx.doi.org/10.1109/CEC.2013.6557738
http://hdl.handle.net/11449/76310
identifier_str_mv 2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.
10.1109/CEC.2013.6557738
2-s2.0-84881575854
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2013 IEEE Congress on Evolutionary Computation, CEC 2013
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1483-1490
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_ 1808129268804222976

Registros relacionados