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dc.contributor.authorQuadri, Dominique
dc.contributor.authorSoutif, Eric
dc.contributor.authorTolla, Pierre
dc.date.accessioned2010-04-13T08:54:03Z
dc.date.available2010-04-13T08:54:03Z
dc.date.issued2009
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/3950
dc.descriptionVoir http://basepub.dauphine.fr/xmlui/handle/123456789/3952
dc.language.isoenen
dc.subjectBranch-and-bounden
dc.subjectSurrogate relaxationen
dc.subjectLinearizationen
dc.subjectSeparable quadratic functionen
dc.subjectInteger programmingen
dc.subject.ddc005en
dc.titleExact solution method to solve large scale integer quadratic multidimensional knapsack problemsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenIn this paper we develop a branch-and-bound algorithm for solving a particular integer quadratic multi-knapsack problem. The problem we study is defined as the maximization of a concave separable quadratic objective function over a convex set of linear constraints and bounded integer variables. Our exact solution method is based on the computation of an upper bound and also includes pre-procedure techniques in order to reduce the problem size before starting the branch-and-bound process. We lead a numerical comparison between our method and three other existing algorithms. The approach we propose outperforms other procedures for large-scaled instances (up to 2000 variables and constraints).en
dc.relation.isversionofjnlnameJournal of Combinatorial Optimization
dc.relation.isversionofjnlvol17en
dc.relation.isversionofjnlissue2en
dc.relation.isversionofjnldate2009-02
dc.relation.isversionofjnlpages157-167en
dc.relation.isversionofdoihttp://dx.doi.org/10.1007/s10878-007-9105-1en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSpringeren
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen


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