Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/669
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dc.contributor.authorKratica, Jozefen_US
dc.contributor.authorTošić, Dušanen_US
dc.contributor.authorFilipović, Vladimiren_US
dc.contributor.authorDugošija, Dordeen_US
dc.date.accessioned2022-08-14T09:49:35Z-
dc.date.available2022-08-14T09:49:35Z-
dc.date.issued2011-12-01-
dc.identifier.issn03540243en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/669-
dc.description.abstractIn this paper, we propose a new genetic encoding for well known Quadratic Assignment Problem (QAP). The new encoding schemes are implemented with appropriate objective function and modified genetic operators. The numerical experiments were carried out on the standard QAPLIB data sets known from the literature. The presented results show that in all cases proposed genetic algorithm reached known optimal solutions in reasonable time.en_US
dc.language.isoenen_US
dc.publisherBeograd : Fakultet organizacionih naukaen_US
dc.relation.ispartofYugoslav Journal of Operations Researchen_US
dc.subjectCombinatorial optimizationen_US
dc.subjectEvolutionary computationen_US
dc.subjectGenetic algorithmen_US
dc.subjectQuadratic assignment problemen_US
dc.titleA new genetic representation for quadratic assignment problemen_US
dc.typeArticleen_US
dc.identifier.doi10.2298/YJOR1102225K-
dc.identifier.scopus2-s2.0-84880818121-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84880818121-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.issn0354-0243en_US
dc.description.rankM51en_US
dc.relation.firstpage225en_US
dc.relation.lastpage238en_US
dc.relation.volume21en_US
dc.relation.issue2en_US
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypeArticle-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0002-5943-8037-
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