Efficient ant colony algorithm based on right pheromone updating and mutation

Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (1): 45-47.

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Efficient ant colony algorithm based on right pheromone updating and mutation

GONG Ben-can^1,2,LI La-yuan²,JIANG Ting-yao¹,WANG Xiang-li²

1.College of Electrical Engineering and Information Technology，China Three Gorges University，Yichang，Hubei 443002，China
2.College of Computer Science and Technology，Wuhan University of Technology，Wuhan 430063，China

Received:1900-01-01 Revised:1900-01-01 Online:2008-01-01 Published:2008-01-01
Contact: GONG Ben-can

基于信息素适量更新与变异的高效蚁群算法

龚本灿^1,2,李腊元²,蒋廷耀¹,汪祥莉²

1.三峡大学电气信息学院，湖北宜昌 443002
2.武汉理工大学计算机学院，武汉 430063

通讯作者: 龚本灿

Abstract

Abstract: To overcome the default of slow convergence speed，precocity and stagnation in the basic ant colony Algorithm（ACA），we proposed an Efficient Ant Colony Algorithm（EACA）.It modifies the rule of updating pheromones in ACA，so that after every round of search，the increment of pheromone can better reflect the quality of a solution to quicken the convergence；In addition，it uses the heuristic mutation to optimize tours，generate disarrangement effect and avoid precocity.Experimental results for solving TSP（Traveling Salesman Problem） show that the proposed algorithm outperforms ACA and ACAGA.

Key words: ant colony algorithm, rule of updating pheromones, mutation, TSP

摘要： 为了克服基本蚁群算法求解速度慢、易于出现早熟和停滞现象的缺陷，提出了一种高效的蚁群算法（EACA）。它修改了基本蚁群算法中信息素的更新规则，使得每轮搜索后信息素的增量能更好地反映解的质量，以加快收敛；另外，它采用了一种启发式变异方法对路径进行优化，以产生搅动效应，避免早熟。以TSP问题为例进行的实验结果表明：提出的算法优于ACA和ACAGA。

关键词: 蚁群算法, 信息素更新规则, 变异, TSP

GONG Ben-can^1,2,LI La-yuan²,JIANG Ting-yao¹,WANG Xiang-li². Efficient ant colony algorithm based on right pheromone updating and mutation[J]. Computer Engineering and Applications, 2008, 44(1): 45-47.

龚本灿^1,2,李腊元²,蒋廷耀¹,汪祥莉². 基于信息素适量更新与变异的高效蚁群算法[J]. 计算机工程与应用, 2008, 44(1): 45-47.

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Efficient ant colony algorithm based on right pheromone updating and mutation

基于信息素适量更新与变异的高效蚁群算法

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