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dc.contributor.authorAraujo, Silvio A. de
dc.contributor.authorArenales, Marcos N.
dc.contributor.authorClark, Alistair R.
dc.date.accessioned2014-05-27T11:22:48Z
dc.date.available2014-05-27T11:22:48Z
dc.date.issued2008-03-01
dc.identifierhttp://dx.doi.org/10.1016/j.cor.2006.05.010
dc.identifier.citationComputers and Operations Research, v. 35, n. 3, p. 916-932, 2008.
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/11449/70313
dc.description.abstractA lot sizing and scheduling problem prevalent in small market-driven foundries is studied. There are two related decision levels: (1) the furnace scheduling of metal alloy production, and (2) moulding machine planning which specifies the type and size of production lots. A mixed integer programming (MIP) formulation of the problem is proposed, but is impractical to solve in reasonable computing time for non-small instances. As a result, a faster relax-and-fix (RF) approach is developed that can also be used on a rolling horizon basis where only immediate-term schedules are implemented. As well as a MIP method to solve the basic RF approach, three variants of a local search method are also developed and tested using instances based on the literature. Finally, foundry-based tests with a real-order book resulted in a very substantial reduction of delivery delays and finished inventory, better use of capacity, and much faster schedule definition compared to the foundry's own practice. © 2006 Elsevier Ltd. All rights reserved.en
dc.format.extent916-932
dc.language.isoeng
dc.relation.ispartofComputers and Operations Research
dc.sourceScopus
dc.subjectLot sizing and scheduling
dc.subjectMeta-heuristics
dc.subjectMixed integer programming
dc.subjectHeuristic algorithms
dc.subjectInteger programming
dc.subjectMetadata
dc.subjectProblem solving
dc.subjectTabu search
dc.subjectMetaheuristics
dc.subjectScheduling
dc.titleLot sizing and furnace scheduling in small foundriesen
dc.typeArtigo
dcterms.licensehttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.contributor.institutionUniversity of the West of England
dc.description.affiliationInstituto de Biociências Letras e Ciências Exatas Departamento de Ciências da Computação e Estatística, Sao Jose do Rio Preto, SP 15054-000
dc.description.affiliationInstituto de Ciências Matemáticas e de Computação Departamento de Matemática Aplicada e Estatística Universidade de São Paulo, Caixa Postal 668, São Carlos, SP 13560-970
dc.description.affiliationFaculty of Computing Engineering and Mathematical Sciences University of the West of England, Bristol, BS16 1QY
dc.identifier.doi10.1016/j.cor.2006.05.010
dc.identifier.wosWOS:000250256100022
dc.rights.accessRightsAcesso restrito
dc.identifier.scopus2-s2.0-34548453509
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
dc.identifier.orcid0000-0002-4762-2048
unesp.author.orcid0000-0002-4762-2048[1]
dc.relation.ispartofjcr2.962
dc.relation.ispartofsjr1,916
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