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An improved ant colony algorithm and its application in TSP

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5 Author(s)
Fengcai Huo ; Sch. of Electr. & Inf. Eng., Daqing Pet. Inst., Daqing, China ; Weijian Ren ; Ruijun Ran ; Yingnan Liu
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The default that the factor of pheromone remnant is constant can make the algorithm fall into the local optimal solution easily, a new factor of pheromone remnant is proposed which is varying with the iterative time. But this can not overcome the local one completely, the bit exchanging mode with the shifting windows is proposed by the analysis in the solution set. Above all an improved ant colony algorithm is got, then it applies in the TSP, the simulation shows that this algorithm can improve the ability of searching global optimization and overcome premature convergence. Comparison with the basic ant colony algorithm shows that the algorithm is effective.

Published in:

Intelligent Control and Automation (WCICA), 2010 8th World Congress on

Date of Conference:

7-9 July 2010

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