BEST-WORST Ant System

摘要：

The BEST-WORST Ant System (BWAS) algorithm discussed in this paper achieves a strong exploitation of the search history by allowing both the best solutions and the worst solutions to change pheromone during the pheromone trail update. It not only makes effective use of the positive feedback of iteration (global)-best ant, but also makes full use of the negative feedback of iteration (global)-worst ant It improves the efficiency significantly. The use of a rather simple mechanism for limiting the strengths of the pheromone trails effectively avoids premature convergence of the search. Experimental results on TSP show that The BWAS algorithm has a better global searching ability, higher convergence speed and solution diversity than that of classical ACO algorithm.

关键词： Ant Colony Optimization Pheromone Traveling salesman problem

作者: Yan Zhang Hao Wang Yonghua Zhang Yun Chen

作者单位: School of Computer and Information Fuyang Teachers College

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Advanced Computer Control(2011年IEEE第三届高端计算机控制国际会议 ICACC2011)

会议地点: 哈尔滨

会议语种:英文

页码: 392-395

在线出版日期: 2011-01-18（万方平台首次上网日期，不代表论文的发表时间）