An Improved Genetic & Ant Colony Optimization Algorithm for Travelling Salesman Problem

摘要：

Ant Colony Algorithm (ACA) and Generation Algorithm (GA) are two bionic optimization algorithm, they are also two powerful and effective algorithms for solving the combination optimization problems, moreover they all were successfully used in traveling salesman problem (TSP). This paper syncretizes two algorithms, meanwhile, a new syncretic method is put forward. The simulation results show that the new algorithm of ACA and GA is better at improving global convergence and quickening the speed of convergence.

关键词： Generation Algorithm Ant Colony Algorithm Mixed Algorithm TSP

作者: Lanlan Kang Wenliang Cao

作者单位: Faculty of Applied Science JiangXi University of Science and Technolo Jiangxi, China Department of Computer Engineering DongGuan Polytechnic Dongguan, Guangdong, China

会议类型: 国际会议

会议名称: Third International Symposium on Information Science and Engineering(第三届信息科学与工程国际会议 ISISE 2010)

会议地点: 上海

会议语种:英文

页码: 498-502

在线出版日期: 2010-12-24（万方平台首次上网日期，不代表论文的发表时间）