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dc.contributor.authorHaouari, Mohamed
dc.contributor.authorSerairi, M.
dc.date.accessioned2012-05-31T10:29:38Z
dc.date.available2012-05-31T10:29:38Z
dc.date.issued2009-10
dc.identifier.issn0305-0548
dc.identifier.urihttp://hdl.handle.net/10679/189
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0305054808002748
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractWe investigate the one-dimensional variable-sized bin-packing problem. This problem requires packing a set of items into a minimum-cost set of bins of unequal sizes and costs. Six optimization-based heuristics for this problem are presented and compared. We analyze their empirical performance on a large set of randomly generated test instances with up to 2000 items and seven bin types. The first contribution of this paper is to provide evidence that a set covering heuristic proves to be highly effective and capable of delivering very-high quality solutions within short CPU times. In addition, we found that a simple subset-sum problem-based heuristic consistently outperforms heuristics from the literature while requir- ing extremely short CPU times.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofComputers & Operations Research
dc.rightsrestrictedAccess
dc.titleHeuristics for the variable sized bin-packing problemen_US
dc.typeArticleen_US
dc.peerreviewedyesen_US
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.ozuauthorHaouari, Mohamed
dc.identifier.volume36
dc.identifier.issue10
dc.identifier.startpage2877
dc.identifier.endpage2884
dc.identifier.wosWOS:000265369200020
dc.identifier.doi10.1016/j.cor.2008.12.016
dc.subject.keywordsBin-packing problemen_US
dc.subject.keywordsHeuristicsen_US
dc.subject.keywordsGenetic algorithmen_US
dc.identifier.scopusSCOPUS:2-s2.0-62549163791
dc.contributor.authorMale1


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