DC FieldValueLanguage
dc.contributor.authorDavidović, Tatjanaen
dc.contributor.authorTeodorović, Dušanen
dc.contributor.authorŠelmić, Milicaen
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/123456789/259-
dc.description.abstractThis paper is an extensive survey of the Bee Colony Optimization (BCO) algorithm, proposed for the first time in 2001. BCO and its numerous variants belong to a class of nature-inspired meta-heuristic methods, based on the foraging habits of honeybees. Our main goal is to promote it among the wide operations research community. BCO is a simple, but effcient meta-heuristic technique that has been successfully applied to many optimization problems, mostly in transport, location and scheduling fields. Firstly, we shall give a brief overview of the meta-heuristics inspired by bees' foraging principles, pointing out the differences between them. Then, we shall provide the detailed description of the BCO algorithm and its modifications, including the strategies for BCO parallelization, and give the preliminary results regarding its convergence. The application survey is elaborated in Part II of our paper.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.subjectForaging of honey bees | Meta-heuristics | Swarm intelligenceen
dc.titleBee Colony Optimization part I: The algorithm overviewen
dc.typeArticleen
dc.identifier.doi10.2298/YJOR131011017Den
dc.identifier.scopus2-s2.0-84924811688en
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Arts-
dc.relation.firstpage33en
dc.relation.lastpage56en
dc.relation.issue1en
dc.relation.volume25en
dc.description.rankM51-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
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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