An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem

摘要：

This paper presents a modified Ant Colony Algorithm (ACA) called route-update ant colony algorithm (RUACA). The research attention is focused on improving the computational efficiency in the TSP problem. A new impact factor is introduced and proved to be effective for reducing the convergence time in the RUACA performance. In order to assess the RUACA performance, a simply supported data set of cities, which was taken as the source data in previous research using traditional ACA and genetic algorithm (GA), is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented RUACA has successfully solved the TSP problem. The results of the proposed algorithm are found to be satisfactory.

关键词： Ant Colony Algorithm Traveling salesman problem Magnetic force

作者: Zhanwei Du Yongjian Yang Yongxiong Sun Chijun Zhang Tuanliang Li

作者单位: College of Computer Science and Technology ,Jilin University, Changchun 130012 China College of Computer Science and Technology ,Jilin University, Changchun 130012 China College of Info

会议类型: 国际会议

会议名称: 2010 International Conference on Advanced Mechanical Engineering(2010年先进机械工程国际学术会议 AME 2010)

会议地点: 洛阳

会议语种:英文

页码: 620-624

在线出版日期: 2010-09-04（万方平台首次上网日期，不代表论文的发表时间）