DC FieldValueLanguage
dc.contributor.authorTeodorović, Dušanen
dc.contributor.authorŠelmić, Milicaen
dc.contributor.authorDavidović, Tatjanaen
dc.date.accessioned2020-04-03T08:16:02Z-
dc.date.available2020-04-03T08:16:02Z-
dc.date.issued2015-01-01en
dc.identifier.issn0354-0243en
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/258-
dc.description.abstractBee Colony Optimization (BCO) is a meta-heuristic method based on foraging habits of honeybees. This technique was motivated by the analogy found between the natural behavior of bees searching for food and the behavior of optimization algorithms searching for an optimum in combinatorial optimization problems. BCO has been successfully applied to various hard combinatorial optimization problems, mostly in transportation, location and scheduling fields. There are some applications in the continuous optimization field that have appeared recently. The main purpose of this paper is to introduce the scientific community more closely with BCO by summarizing its existing successful applications.en
dc.publisherFaculty of Organizational Sciences, Belgrade-
dc.relationMathematical Modelas and Optimization Methods on Large-Scale Systems-
dc.relationGraph theory and mathematical programming with applications in chemistry and computer science-
dc.relationComputational Intelligence Techniques in Transportation and Communication Planning and Traffic Control-
dc.relation.ispartofYugoslav Journal of Operations Researchen
dc.subjectCombinatorial optimization | Location | Meta-heuristic methods | Routing | Scheduling problems | Swarm intelligenceen
dc.titleBee colony optimization Part II: The application surveyen
dc.typeArticleen
dc.identifier.doi10.2298/YJOR131029020Ten
dc.identifier.scopus2-s2.0-84939483130en
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Arts-
dc.relation.firstpage185en
dc.relation.lastpage219en
dc.relation.issue2en
dc.relation.volume25en
dc.description.rankM51-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.project.funderNIH-
crisitem.project.projectURLhttp://www.mi.sanu.ac.rs/novi_sajt/research/projects/174010e.php-
crisitem.project.projectURLhttp://www.mi.sanu.ac.rs/novi_sajt/research/projects/174033e.php-
crisitem.project.fundingProgramDirectorate for Engineering-
crisitem.project.fundingProgramDirectorate for Computer & Information Science & Engineering-
crisitem.project.fundingProgramNATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES-
crisitem.project.openAireinfo:eu-repo/grantAgreement/NSF/Directorate for Engineering/1740103-
crisitem.project.openAireinfo:eu-repo/grantAgreement/NSF/Directorate for Computer & Information Science & Engineering/1740333-
crisitem.project.openAireinfo:eu-repo/grantAgreement/NIH/NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES/5R01GM036002-14-
crisitem.author.orcid0000-0001-9561-5339-
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