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dc.contributor.authorDavidović, Tatjanaen_US
dc.date.accessioned2020-12-16T10:35:38Z-
dc.date.available2020-12-16T10:35:38Z-
dc.date.issued2020-
dc.identifier.urihttp://researchrepository.mi.sanu.ac.rs/handle/123456789/4507-
dc.description.abstractArtificial Intelligence (AI) is a modern field in computer science that involves automatic learning processes. It usually means that computers are programmed to make some decisions based on the input parameter values as well as on the previous experience. Decision making problems were usually not considered as optimization problems, however, recent trends in merging optimization and AI changed that perspective.Metaheuristics were successfully applied to many decision making problems, such as training of Artificial Neural Networks, medical therapy determination, clustering, feature selection, and satisfiability problems. Several recent papers, considering the application of Bee Colony Optimization (BCO) to the decision making problems,are reviewed here with an emphasis on the author’s results.en_US
dc.publisherFaculty of Transport and Traffic Engineering, University of Belgradeen_US
dc.subjectArtificial intelligence | Decision support systems | Optimization problems | Metaheuristicsen_US
dc.titleBee Colony Optimization for Decision Making Problemsen_US
dc.typeConference Paperen_US
dc.relation.conferenceXLVII Symposium on Operational Research, SYMOPIS 2020, Virtual conference, Sept. 20-23, 2020en_US
dc.identifier.urlhttp://www.mi.sanu.ac.rs/~tanjad/SYMOPIS2020-BCOforDM.pdf-
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Artsen_US
dc.relation.firstpage138-
dc.relation.lastpage143-
dc.description.rankM63-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Paper-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.orcid0000-0001-9561-5339-
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