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dc.contributor.authorDuarte, Abrahamen
dc.contributor.authorPantrigo, Juanen
dc.contributor.authorPardo, Eduardoen
dc.contributor.authorMladenović, Nenaden
dc.date.accessioned2020-05-02T16:42:00Z-
dc.date.available2020-05-02T16:42:00Z-
dc.date.issued2015-11-01en
dc.identifier.issn0925-5001en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/2439-
dc.description.abstractSolutions to real-life optimization problems usually have to be evaluated considering multiple conflicting objectives. These kind of problems, known as multi-objective optimization problems, have been mainly solved in the past by using evolutionary algorithms. In this paper, we explore the adaptation of the Variable Neighborhood Search (VNS) metaheuristic to solve multi-objective combinatorial optimization problems. In particular, we describe how to design the shake procedure, the improvement method and the acceptance criterion within different VNS schemas (Reduced VNS, Variable Neighborhood Descent and General VNS), when two or more objectives are considered. We validate these proposals over two multi-objective combinatorial optimization problems.en
dc.publisherSpringer Link-
dc.relation.ispartofJournal of Global Optimizationen
dc.subjectAntibandwidth | Cutwidth | Knapsack | Multi-objective optimization | Multi-objective VNSen
dc.titleMulti-objective variable neighborhood search: an application to combinatorial optimization problemsen
dc.typeArticleen
dc.identifier.doi10.1007/s10898-014-0213-zen
dc.identifier.scopus2-s2.0-84943360970en
dc.relation.firstpage515en
dc.relation.lastpage536en
dc.relation.issue3en
dc.relation.volume63en
dc.description.rankM21-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.orcid0000-0001-6655-0409-
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