You are in the accessibility menu

Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/76310
Full metadata record
DC FieldValueLanguage
dc.contributor.authorToledo, Claudio F. M.-
dc.contributor.authorHossomi, Marcelo Y. B.-
dc.contributor.authorDa Silva Arantes, Márcio-
dc.contributor.authorFranca, Paulo Morelato-
dc.date.accessioned2014-05-27T11:30:11Z-
dc.date.accessioned2016-10-25T18:52:45Z-
dc.date.available2014-05-27T11:30:11Z-
dc.date.available2016-10-25T18:52:45Z-
dc.date.issued2013-08-21-
dc.identifierhttp://dx.doi.org/10.1109/CEC.2013.6557738-
dc.identifier.citation2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.-
dc.identifier.urihttp://hdl.handle.net/11449/76310-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/76310-
dc.description.abstractThe 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.en
dc.format.extent1483-1490-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectgenetic algorithm-
dc.subjecthybrid metaheuristic-
dc.subjectlot-sizing-
dc.subjectmulti-level-
dc.subjectCapacitated lot sizing problem-
dc.subjectComputational results-
dc.subjectHybrid Meta-heuristic-
dc.subjectLot sizing-
dc.subjectMixed-Integer Programming-
dc.subjectBenchmarking-
dc.subjectHeuristic methods-
dc.subjectInteger programming-
dc.subjectGenetic algorithms-
dc.titleGenetic algorithm, MIP and improvement heuristic applied to the MLCLP with backloggingen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationInstitute of Mathematics and Computer Science University of São Paulo, São Carlos-
dc.description.affiliationUNESP Dept. of Mathematics and Computing-
dc.description.affiliationUnespUNESP Dept. of Mathematics and Computing-
dc.identifier.doi10.1109/CEC.2013.6557738-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartof2013 IEEE Congress on Evolutionary Computation, CEC 2013-
dc.identifier.scopus2-s2.0-84881575854-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

There are no files associated with this item.
Show simple item record Show full item record   View Statistics
 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.