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dc.contributor.authorToledo, C. F. M.-
dc.contributor.authorFranca, P. M.-
dc.contributor.authorMorabito, R.-
dc.contributor.authorKimms, A.-
dc.identifier.citationInternational Journal of Production Research. Abingdon: Taylor & Francis Ltd, v. 47, n. 11, p. 3097-3119, 2009.-
dc.description.abstractThis paper introduces an evolutionary algorithm as a procedure to solve the Synchronized and Integrated Two-Level Lot Sizing and Scheduling Problem (SITLSP). This problem can be found in some industrial settings, mainly soft drink companies, where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot-sizing and scheduling of raw materials in tanks and soft drinks in bottling lines, where setup costs and times depend on the previous items stored and bottled. A multi-population genetic algorithm approach with a novel representation of solutions for individuals and a hierarchical ternary tree structure for populations is proposed. Computational tests include comparisons with an exact approach for small-to-moderate-sized instances and with real-world production plans provided by a manufacturer.en
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
dc.publisherTaylor & Francis Ltd-
dc.sourceWeb of Science-
dc.subjectlot-sizing and schedulingen
dc.subjectproduction planningen
dc.subjectcombinatorial optimizationen
dc.subjectgenetic algorithmen
dc.subjectsoft drink manufacturingen
dc.titleMulti-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problemen
dc.contributor.institutionUniv Duisburg Essen-
dc.contributor.institutionUniversidade Federal de Lavras (UFLA)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)-
dc.description.affiliationUniv Duisburg Essen, Dept Technol & Operat Management, D-47048 Duisburg, Germany-
dc.description.affiliationUniversidade Federal de Lavras (UFLA), Dept Ciência Computacao, BR-37200000 Lavras, MG, Brazil-
dc.description.affiliationUniv Estadual Paulista, Dept Matemat Estat & Computacao, Fac Ciencias & Tecnol, BR-19060900 Presidente Prudente, SP, Brazil-
dc.description.affiliationUniversidade Federal de São Carlos (UFSCar), Dept Engn Producao, BR-13565905 São Carlos, SP, Brazil-
dc.description.affiliationUnespUniv Estadual Paulista, Dept Matemat Estat & Computacao, Fac Ciencias & Tecnol, BR-19060900 Presidente Prudente, SP, Brazil-
dc.description.sponsorshipIdFAPESP: 00/02609-2-
dc.description.sponsorshipIdCNPq: 303956/2003-8-
dc.description.sponsorshipIdCNPq: 522973/95-7-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofInternational Journal of Production Research-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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