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dc.contributor.authorBrimberg, Jacken
dc.contributor.authorHansen, Pierreen
dc.contributor.authorMladenović, Nenaden
dc.date.accessioned2020-05-02T16:42:09Z-
dc.date.available2020-05-02T16:42:09Z-
dc.date.issued2010-01-01en
dc.identifier.issn1619-4500en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/2507-
dc.description.abstractEmpirical evidence demonstrates that when the same local search operator is used, variable neighborhood search consistently outperforms random multistart local search on all types of combinatorial and global optimization problems tested. In this paper we suggest that this superiority in performance may be explained by the distribution of the attraction basins around a current solution as a function of the distance from the solution. We illustrate with a well-known instance of the multisource Weber problem that the "attraction probabilities" for finding better solutions can be orders of magnitude larger in neighborhoods that are close to the current solution. The paper also discusses the global convergence properties of both general methods in the context of attraction probabilities.en
dc.publisherSpringer Link-
dc.relation.ispartof4OR : A Quarterly Journal of Operations Researchen
dc.subjectAttraction probabilities | Continuous location | Convergence | Metaheuristics | Variable neighborhood searchen
dc.titleAttraction probabilities in variable neighborhood searchen
dc.typeArticleen
dc.identifier.doi10.1007/s10288-009-0108-xen
dc.identifier.scopus2-s2.0-77952822571en
dc.relation.firstpage181en
dc.relation.lastpage194en
dc.relation.issue2en
dc.relation.volume8en
dc.description.rankM23-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.orcid0000-0001-6655-0409-
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