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dc.contributor.authorMladenović, Nenaden
dc.contributor.authorDražić, Milanen
dc.contributor.authorKovačevic-Vujčić, Veraen
dc.contributor.authorČangalović, Mirjanaen
dc.date.accessioned2020-05-02T16:42:11Z-
dc.date.available2020-05-02T16:42:11Z-
dc.date.issued2008-12-16en
dc.identifier.issn0377-2217en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/2521-
dc.description.abstractWe suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Different neighborhoods and distributions, induced from different metrics are ranked and used to get random points in the shaking step. We also propose VNS for solving constrained optimization problems. The constraints are handled using exterior point penalty functions within an algorithm that combines sequential and exact penalty transformations. The extensive computer analysis that includes the comparison with genetic algorithm and some other approaches on standard test functions are given. With our approach we obtain encouraging results.en
dc.publisherElsevier-
dc.relation.ispartofEuropean Journal of Operational Researchen
dc.subjectGlobal optimization | Metaheuristics | Nonlinear programming | Variable neighborhood searchen
dc.titleGeneral variable neighborhood search for the continuous optimizationen
dc.typeArticleen
dc.identifier.doi10.1016/j.ejor.2006.12.064en
dc.identifier.scopus2-s2.0-44649168278en
dc.relation.firstpage753en
dc.relation.lastpage770en
dc.relation.issue3en
dc.relation.volume191en
dc.description.rankM21-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
crisitem.author.orcid0000-0001-6655-0409-
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