Resolution of TSP based on improved Ant Colony Algorithm

被引：0
|
作者：
Liu, Chunbo [1 ]
Wang, Wenxia [1 ]
Pan, Feng [1 ]
机构：
[1] So Yangtze Univ, Sch Commun & Control Engn, WuXi 214122, Jiangsu, Peoples R China
来源：
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS | 2007年 / 14卷
关键词：
Ant Colony Algorithm; pheromone; MATLAB; Chinese Traveling Salesman Problem(CTSP);
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The pheromone's Volatilizing tactics is changed to improve the disadvantages of ant colony algorithm such as slow convergence speed and taking partial solution as optimum solution. The volatilizing speed of pheromone is not a constant but an adaptive variable in search for optimum solution. Among MATLAB's simulation of CTSP, the volatilizing speed of pheromone is changed adaptively in order to suppress positive feedback, expand feasible solution scope that can avoid algorithm's premature, and improve solution's quality. The result is 15602 at 46(th) generation at every time almost that can prove the algorithm's good discovering ability that provides some theory for further real application.
引用
收藏
页码：387 / 390
页数：4
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