An Improved Ant Colony Algorithm for Traveling Salesmen Problem
The traditional Ant System Algorithm has some deficiencies, such as long computation time and easy to fall in local best. In order to solve these problems, a new version of Ant System based on Pheromone Mutation (PMAS) is presented. When the searching process has the trends of convergence, the new algorithm will change the pheromone in the path dynamically based on the idea of mutation, so that the search process will fly from the local best. Moreover, a new kind of pheromone updating rule which combines the global information and local information is also presented. The new algorithm is applied to solve many traveling salesmen problems. Experimental results show that the algorithm has much better capacity in global optimization than the traditional ant system algorithms.
Ant System Traveling Salesmen Problem Pheromone mutation Pheromone Updating Rule
Yang Zhi ming Peng Xi yuan Peng Yu
Department of Automatic Test and Control, P.O.box 3033, Harbin Institute of Technology, 150080
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）