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dc.contributor.authorBazgan, Cristina
dc.contributor.authorHugot, Hadrien
dc.contributor.authorVanderpooten, Daniel
dc.date.accessioned2010-01-14T09:28:52Z
dc.date.available2010-01-14T09:28:52Z
dc.date.issued2009
dc.identifier.issn0305-0548
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/2926
dc.language.isoenen
dc.subjectDynamic programming
dc.subjectDominance relations
dc.subjectEfficient solutions
dc.subjectNon-dominated criterion vectors
dc.subjectCombinatorial optimization
dc.subjectMulti-objective knapsack problem
dc.subject.ddc511en
dc.titleSolving efficiently the 0-1 multi-objective knapsack problem
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenIn this paper, we present an approach, based on dynamic programming, for solving the 0–1 multi-objective knapsack problem. The main idea of the approach relies on the use of several complementary dominance relations to discard partial solutions that cannot lead to new non-dominated criterion vectors. This way, we obtain an efficient method that outperforms the existing methods both in terms of CPU time and size of solved instances.Extensive numerical experiments on various types of instances are reported. A comparison with other exact methods is also performed. In addition, for the first time to our knowledge, we present experiments in the three-objective case.
dc.relation.isversionofjnlnameComputers and Operations Research
dc.relation.isversionofjnlvol36
dc.relation.isversionofjnlissue1
dc.relation.isversionofjnldate2009
dc.relation.isversionofjnlpages260-279
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/j.cor.2007.09.009
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherElsevier
dc.subject.ddclabelPrincipes généraux des mathématiquesen
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2016-10-06T09:45:17Z


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