dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorFiorotto, Diego Jacinto
dc.creatorAraujo, Silvio Alexandre de
dc.creatorJans, Raf
dc.date2016-03-02T13:04:24Z
dc.date2016-10-25T21:33:28Z
dc.date2016-03-02T13:04:24Z
dc.date2016-10-25T21:33:28Z
dc.date2015
dc.date.accessioned2017-04-06T10:07:13Z
dc.date.available2017-04-06T10:07:13Z
dc.identifierComputers & Operations Research, v. 63, p. 136-148, 2015.
dc.identifier0305-0548
dc.identifierhttp://hdl.handle.net/11449/135782
dc.identifierhttp://acervodigital.unesp.br/handle/11449/135782
dc.identifier10.1016/j.cor.2015.04.015
dc.identifier0000-0002-4762-2048
dc.identifier9919773182316062
dc.identifier2533297944605843
dc.identifierhttp://dx.doi.org/10.1016/j.cor.2015.04.015
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/946288
dc.descriptionWe consider the capacitated lot sizing problem with multiple items, setup time and unrelated parallel machines, and apply Dantzig–Wolfe decomposition to a strong reformulation of the problem. Unlike in the traditional approach where the linking constraints are the capacity constraints, we use the flow constraints, i.e. the demand constraints, as linking constraints. The aim of this approach is to obtain high quality lower bounds. We solve the master problem applying two solution methods that combine Lagrangian relaxation and Dantzig–Wolfe decomposition in a hybrid form. A primal heuristic, based on transfers of production quantities, is used to generate feasible solutions. Computational experiments using data sets from the literature are presented and show that the hybrid methods produce lower bounds of excellent quality and competitive upper bounds, when compared with the bounds produced by other methods from the literature and by a high-performance MIP software.
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languagepor
dc.relationComputers & Operations Research
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectLot sizing
dc.subjectParallel machines
dc.subjectReformulation
dc.subjectHybrid methods
dc.subjectDantzig–Wolfe decomposition
dc.subjectLagrangian relaxation
dc.subjectProblema de dimensionamento de lotes
dc.subjectRelaxação lagrangiana
dc.subjectGeração de colunas
dc.titleHybrid methods for lot sizing on parallel machines
dc.typeOtro


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