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dc.contributor.authorGramani, Maria Cristina N.-
dc.contributor.authorFranca, Paulo M.-
dc.contributor.authorArenales, Marcos N.-
dc.date.accessioned2014-05-20T15:31:26Z-
dc.date.accessioned2016-10-25T18:07:15Z-
dc.date.available2014-05-20T15:31:26Z-
dc.date.available2016-10-25T18:07:15Z-
dc.date.issued2011-09-01-
dc.identifierhttp://dx.doi.org/10.1016/j.jfranklin.2010.05.010-
dc.identifier.citationJournal of The Franklin Institute-engineering and Applied Mathematics. Oxford: Pergamon-Elsevier B.V. Ltd, v. 348, n. 7, p. 1523-1536, 2011.-
dc.identifier.issn0016-0032-
dc.identifier.urihttp://hdl.handle.net/11449/40568-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/40568-
dc.description.abstractTwo fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.en
dc.format.extent1523-1536-
dc.language.isoeng-
dc.publisherPergamon-Elsevier B.V. Ltd-
dc.sourceWeb of Science-
dc.subjectLot sizingen
dc.subjectCutting stocken
dc.subjectColumn generation techniqueen
dc.subjectLinear optimization approachen
dc.titleA linear optimization approach to the combined production planning modelen
dc.typeoutro-
dc.contributor.institutionInsper Inst Educ & Res-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.description.affiliationInsper Inst Educ & Res, BR-04546042 São Paulo, Brazil-
dc.description.affiliationUniv Estadual Paulista, FCT, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
dc.description.affiliationUniv São Paulo, ICMC, BR-13560970 São Carlos, SP, Brazil-
dc.description.affiliationUnespUniv Estadual Paulista, FCT, UNESP, BR-19060900 Presidente Prudente, SP, Brazil-
dc.identifier.doi10.1016/j.jfranklin.2010.05.010-
dc.identifier.wosWOS:000293960600025-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofJournal of The Franklin Institute-engineering and Applied Mathematics-
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