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dc.contributor.authorLin, Lingzh_CN
dc.contributor.authorDong, Huailinzh_CN
dc.contributor.authorWu, Qingfengzh_CN
dc.contributor.authorXu, Tianmaozh_CN
dc.contributor.author董槐林zh_CN
dc.contributor.author吴清锋zh_CN
dc.date.accessioned2015-07-22T02:16:23Z
dc.date.available2015-07-22T02:16:23Z
dc.date.issued2011zh_CN
dc.identifier.citationProceedings - 2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2011, 2011,2:453-456zh_CN
dc.identifier.other20114314447967zh_CN
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/85860
dc.descriptionConference Name:2011 6th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2011. Conference Address: Chongqing, China. Time:August 20, 2011 - August 22, 2011.zh_CN
dc.descriptionIEEE Beijing Section; Chongqing Computer Federation; Chongqing University; Southwest University; Chongqing Three Gorges Universityzh_CN
dc.description.abstractAnt colony algorithm is a new algorithm of heuristic bionic calculation. Now, it has been widely applied in many fields of combinatorial optimization. This paper elaborates the basic principle and mathematical model of typical ant colony algorithm for solving the traveling salesman problem, and analyzes impact of the optimal parameters to the performance of algorithm. Based on its shortages, an improved algorithm by dynamically adjusting parameters is proposed. Finally, the paper gives the simulation result, and it indicates the improved algorithm has a better performance. ? 2011 IEEE.zh_CN
dc.language.isoen_USzh_CN
dc.publisherIEEE Computer Societyzh_CN
dc.source.urihttp://dx.doi.org/10.1109/ITAIC.2011.6030371zh_CN
dc.subjectCombinatorial optimizationzh_CN
dc.subjectInformation technologyzh_CN
dc.subjectMathematical modelszh_CN
dc.subjectParameter estimationzh_CN
dc.subjectProblem solvingzh_CN
dc.subjectTraveling salesman problemzh_CN
dc.titleResearch and improvement of ant colony algorithm based on TSPzh_CN
dc.typeConferencezh_CN


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