DC FieldValueLanguage
dc.contributor.authorBrimberg, Jacken
dc.contributor.authorMladenović, Nenaden
dc.contributor.authorUrošević, Draganen
dc.contributor.authorNgai, Ericen
dc.date.accessioned2020-05-01T20:13:56Z-
dc.date.available2020-05-01T20:13:56Z-
dc.date.issued2009-11-01en
dc.identifier.issn0305-0548en
dc.description.abstractThis paper presents a variable neighborhood search (VNS) heuristic for solving the heaviest k-subgraph problem. Different versions of the heuristic are examined including 'skewed' VNS and a combination of a constructive heuristic followed by VNS. Extensive computational experiments are performed on a series of large random graphs as well as several instances of the related maximum diversity problem taken from the literature. The results obtained by VNS were consistently the best over a number of other heuristics tested.en
dc.publisherElsevier-
dc.relation.ispartofComputers and Operations Researchen
dc.subjectCombinatorial optimization | Heaviest k-subgraph | Maximum diversity | Metaheuristics | Variable neighborhood searchen
dc.titleVariable neighborhood search for the heaviest k-subgraphen
dc.typeArticleen
dc.identifier.doi10.1016/j.cor.2008.12.020en
dc.identifier.scopus2-s2.0-64849113019en
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Arts-
dc.relation.firstpage2885en
dc.relation.lastpage2891en
dc.relation.issue11en
dc.relation.volume36en
dc.description.rankM21a-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.orcid0000-0001-6655-0409-
crisitem.author.orcid0000-0003-3607-6704-
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