dc.creatorCavalcante, VF
dc.creatorde Souza, CC
dc.creatorLucena, A
dc.date2008
dc.dateJUN
dc.date2014-07-30T13:42:43Z
dc.date2015-11-26T17:27:36Z
dc.date2014-07-30T13:42:43Z
dc.date2015-11-26T17:27:36Z
dc.date.accessioned2018-03-29T00:14:44Z
dc.date.available2018-03-29T00:14:44Z
dc.identifierComputers & Operations Research. Pergamon-elsevier Science Ltd, v. 35, n. 6, n. 1963, n. 1981, 2008.
dc.identifier0305-0548
dc.identifierWOS:000251294600014
dc.identifier10.1016/j.cor.2006.10.009
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/53689
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/53689
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1284838
dc.descriptionRelax-and-Cut algorithms offer an alternative to strengthen Lagrangian relaxation bounds. The main idea behind these algorithms is to dynamically select and dualize inequalities (cuts) within a Lagrangian relaxation framework. This paper proposes a Relax-and-Cut algorithm for the Set Partitioning Problem. Computational tests are reported for benchmark instances from the literature. For Set Partitioning instances with integrality gaps, a variant of the classical Lagrangian relaxation is often used in the literature. It introduces a knapsack constraint to the standard formulation of the problem. Our results indicate that the proposed Relax-and-Cut algorithm outperforms the latter approach in terms of lower bound quality. Furthermore, it turns out to be very competitive in terms of CPU time. Decisive in achieving that performance was the implementation of dominance rules to manage inequalities in the cut pool. The Relax-and-Cut framework proposed here could also be used as a preprocessing tool for Linear Integer Programming solvers. Computational experiments demonstrated that the combined use of our framework and XPRESS improved the performance of that Linear Integer Programming solver for the test sets used in this study. (c) 2006 Elsevier Ltd. All rights reserved.
dc.description35
dc.description6
dc.description1963
dc.description1981
dc.languageen
dc.publisherPergamon-elsevier Science Ltd
dc.publisherOxford
dc.publisherInglaterra
dc.relationComputers & Operations Research
dc.relationComput. Oper. Res.
dc.rightsfechado
dc.rightshttp://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy
dc.sourceWeb of Science
dc.subjectLagrangian relaxation
dc.subjectcutting planes
dc.subjectset partitioning
dc.subjectRelax-and-Cut algorithms
dc.subjectCrew Scheduling Problems
dc.subjectSurrogate Duality
dc.subjectCovering Problem
dc.titleA Relax-and-Cut algorithm for the set partitioning problem
dc.typeArtículos de revistas


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