Parameter Optimization of Ant Colony Algorithm Based on Particle Swarm Optimization

摘要：

By combining the ant colony algorithm with particle swarm optimization algorithm,a method of optimum parameter selection was proposed.In this study,the parameters were set as the position information of particle swanL Then the algorithm was applied to the traveling salesman problem(TSP),and a fitness evaluation function Was designed to evaluate the performance of the algorithm solution.Finally,the particles were guided to the direction of a higher fitness.This hybrid algorithm avoids using artificial experience or repeating trials in selecting parameters.Using particle swarm optimization algorithm to find the best set of parameters,we demonstrate the good performance of ant colony algorithm in finding solutions to the TSP.

作者: Yuntao Dai Liqiang Liu Shujuan Wang

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 1266-1269

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）