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Study of parametric relation in ant colony optimization approach to traveling salesman problem

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dc.contributor.authorLuo, Xuyao-
dc.contributor.authorYu, Fang-
dc.contributor.authorZhang, Jun-
dc.date.accessioned2023-12-08T09:32:09Z-
dc.date.available2023-12-08T09:32:09Z-
dc.date.issued2006-08-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/115846-
dc.description.abstractPresetting control parameters of algorithms are important to ant colony optimization (AGO). This paper presents an investigation into the relationship of algorithms performance and the different control parameter settings. Two tour building methods are used in this paper including the max probability selection and the roulette wheel selection. Four parameters are used, which are two control parameters of transition probability α and β, pheromone decrease factor p, and proportion factor q0 in building methods. By simulated result analysis, the parameter selection rule will be given. © Springer-Verlag Berlin Heidelberg 2006.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherSpringer Verlag-
dc.titleStudy of parametric relation in ant colony optimization approach to traveling salesman problem-
dc.typeArticle-
dc.publisher.location독일-
dc.identifier.doi10.1007/11816102_3-
dc.identifier.scopusid2-s2.0-33749581521-
dc.identifier.wosid000240085400003-
dc.identifier.bibliographicCitationConference proceedings © 2006 Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006, Proceedings, Part III, v.4115 , pp 22 - 32-
dc.citation.titleConference proceedings © 2006 Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Kunming, China, August 16-19, 2006, Proceedings, Part III-
dc.citation.volume4115-
dc.citation.startPage22-
dc.citation.endPage32-
dc.type.docTypeConference paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.subject.keywordPlusNEURAL-NETWORKS-
dc.subject.keywordPlusPOLYNOMIALS-
dc.subject.keywordPlusALGORITHMS-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusROOTS-
dc.identifier.urlhttps://link.springer.com/chapter/10.1007/11816102_3?utm_source=getftr&utm_medium=getftr&utm_campaign=getftr_pilot-
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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