Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: a comparison study

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dc.contributor.authorFerreira, D.
dc.contributor.authorFranca, P. M. [UNESP]
dc.contributor.authorKimms, A.
dc.contributor.authorMorabito, R.
dc.contributor.authorRangel, S. [UNESP]
dc.contributor.authorToledo, C. F. M.
dc.contributor.authorXhafa, F
dc.contributor.authorAbraham, A
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniv Duisburg Essen
dc.contributor.institutionUniversidade Federal de Lavras (UFLA)
dc.date.accessioned2023-07-29T11:51:31Z
dc.date.available2023-07-29T11:51:31Z
dc.date.issued2008-01-01
dc.description.abstractThis chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach.en
dc.description.affiliationUniv Fed Sao Carlos, Dept Engn Producao, BR-13565905 Sao Carlos, SP, Brazil
dc.description.affiliationUniv Estadual Paulista, Dept Matemat Estatist & Computacao, BR-19060400 Presidente Prudente, SP, Brazil
dc.description.affiliationUniv Duisburg Essen, Dept Technol & Operat Management, D-47048 Duisburg, Germany
dc.description.affiliationUniv Estadual Paulista, Dept Ciencia Computacao & Estatist, BR-15054000 Sj Do Rio Preto, SP, Brazil
dc.description.affiliationUniv Fed Lavras, Dept Ciencia Computacao, BR-37200000 Lavras, MG, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Dept Matemat Estatist & Computacao, BR-19060400 Presidente Prudente, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Dept Ciencia Computacao & Estatist, BR-15054000 Sj Do Rio Preto, SP, Brazil
dc.format.extent169-210
dc.identifier.citationMetaheuristics for Scheduling in Industrial and Manufacturing Applications. Berlin: Springer-verlag Berlin, v. 128, p. 169-210, 2008.
dc.identifier.issn1860-949X
dc.identifier.urihttp://hdl.handle.net/11449/245322
dc.identifier.wosWOS:000275045100008
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofMetaheuristics For Scheduling In Industrial And Manufacturing Applications
dc.sourceWeb of Science
dc.subjectTwo-level Production Planning
dc.subjectLot Sizing
dc.subjectScheduling
dc.subjectSoft Drinks Industry
dc.subjectGenetic Algorithm
dc.subjectMemetic Algorithm
dc.titleHeuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: a comparison studyen
dc.typeArtigo
dcterms.licensehttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dcterms.rightsHolderSpringer
unesp.departmentMatemática e Computação - FCTpt

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