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《Journal of Guangxi University(Natural Science Edition)》 2008-S1
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Stuty on some improvement strategies of ant colony algorithm for solving TSP

LAO Juan,WEI Wen-dai,WU Chao-kui (College of Computer Science and Electronic Information,Guangxi University,Nanning Guangxi 530004,China)  
Ant colony algorithm is a bionic intelligence algorithm which has good performance for solving TSP,but it has the shortcoming of long running time and easily getting into local best solution,so the algorithm would fall into stagnation state and cannot find the global best solution.The experiments show that the use of candidate set and local searching strategies can improve the solution quality,and the solving speed is evidently faster.Through the use of pheromone mutation and restart strategie,the algorithm can enhance the variedness of tour exploration,keep tour exploration at a reasonable level,efficiently avoidd falling into stagnation state,and find the global best solution at last.
【CateGory Index】: TP301.6
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【Citations】
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【Co-citations】
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1 JI Jun-zhong HUANG Zhen LIU Chun-nian (Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology,Beijing University of Technology,Beijing 100022,China);An Ant Colony Algorithm Based on Clustering and Partition Optimization[J];Journal of Beijing University of Technology;2008-04
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