DC FieldValueLanguage
dc.contributor.authorHansen, Pierreen
dc.contributor.authorMladenović, Nenaden
dc.contributor.authorPerez-Britos, Dionisioen
dc.date.accessioned2020-05-02T16:42:16Z-
dc.date.available2020-05-02T16:42:16Z-
dc.date.issued2001-07-01en
dc.identifier.issn1381-1231en
dc.description.abstractThe recent Variable Neighborhood Search (VNS) metaheuristic combines local search with systematic changes of neighborhood in the descent and escape from local optimum phases. When solving large instances of various problems, its efficiency may be enhanced through decomposition. The resulting two level VNS, called Variable Neighborhood Decomposition Search (VNDS), is presented and illustrated on the p-median problem. Results on 1400, 3038 and 5934 node instances from the TSP library show VNDS improves notably upon VNS in less computing time, and gives much better results than Fast Interchange (FI), in the same time that FI takes for a single descent. Moreover, Reduced VNS (RVNS), which does not use a descent phase, gives results similar to those of FI in much less computing time.en
dc.publisherSpringer Link-
dc.relation.ispartofJournal of Heuristicsen
dc.subjectDecomposition | Metaheuristic | Variable neighborhood search | Y-medianen
dc.titleVariable neighborhood decomposition searchen
dc.typeArticleen
dc.identifier.doi10.1023/A:1011336210885en
dc.identifier.scopus2-s2.0-0035396750en
dc.relation.firstpage335en
dc.relation.lastpage350en
dc.relation.issue4en
dc.relation.volume7en
dc.description.rankM22-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.orcid0000-0001-6655-0409-
Show simple item record

SCOPUSTM   
Citations

224
checked on Nov 27, 2022

Page view(s)

34
checked on Nov 28, 2022

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.