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Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/2783
DC FieldValueLanguage
dc.contributor.authorDrakulić, Den_US
dc.contributor.authorMarić, Miroslaven_US
dc.contributor.authorTakači, Aleksandar Aen_US
dc.date.accessioned2025-10-20T08:26:07Z-
dc.date.available2025-10-20T08:26:07Z-
dc.date.issued2012-
dc.identifier.urihttps://research.matf.bg.ac.rs/handle/123456789/2783-
dc.description.abstractThe Maximal covering location problem (MCLP) represents a very popular and important optimization problem. The MCLP is NP-hard problem and there are many heuristics for solving it, like Tabu search, Genetic algorithm, Lagrangian relaxation, etc.. This paper describes a new approach to solving MCLP by using a Particle Swarm Optimization (PSO) method. At the end, the paper presents the results of computational tests of this approach on several public instances of MCPL.en_US
dc.language.isoenen_US
dc.publisherRuse : Rusenskij universiteten_US
dc.titleSolving Maximal Covering Location Problem (MCLP) by Using the Particle Swarm Optimization (PSO) Methoden_US
dc.typeConference Objecten_US
dc.relation.conferenceScientific Conference RU&SU 12 - Mathematics, Informatics, Physics (2012 ; Ruse)en_US
dc.relation.publicationScientific Conference RU&SU 12 - Mathematics, Informatics, Physics, Proceedingsen_US
dc.identifier.urlhttp://conf.uni-ruse.bg/bg/docs/cp12/6.1/10.1051/0004-6361/2011186946.1-2.pdf-
dc.description.rankM33en_US
dc.relation.firstpage19en_US
dc.relation.lastpage22en_US
item.openairetypeConference Object-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
crisitem.author.deptInformatics and Computer Science-
crisitem.author.orcid0000-0001-7446-0577-
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