Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/576
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dc.contributor.authorMarić, Miroslaven_US
dc.date.accessioned2022-08-13T14:52:03Z-
dc.date.available2022-08-13T14:52:03Z-
dc.date.issued2010-01-01-
dc.identifier.issn13359150en
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/576-
dc.description.abstractIn this paper a new evolutionary approach for solving the multi-level uncapacitated facility location problem (MLUFLP) is presented. Binary encoding scheme is used with appropriate objective function containing dynamic programming approach for finding sequence of located facilities on each level to satisfy clients' demands. The experiments were carried out on the modified standard single level facility location problem instances. Genetic algorithm (GA) reaches all known optimal solutions for smaller dimension instances, obtained by total enumeration and CPLEX solver. Moreover, all optimal/best known solutions were reached by genetic algorithm for a single-level variant of the problem.en
dc.relation.ispartofComputing and Informaticsen
dc.subjectEvolutionary approachen
dc.subjectFacility locationen
dc.subjectGenetic algorithmsen
dc.titleAn efficient genetic algorithm for solving the multi-level uncapacitated facility location problemen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-77954777523-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/77954777523-
dc.contributor.affiliationInformatics and Computer Scienceen_US
dc.relation.firstpage183en
dc.relation.lastpage201en
dc.relation.volume29en
dc.relation.issue2en
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0001-7446-0577-
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