基于边缘搜索的蚁群算法  

Ant Colony Optimization Based On Edge Search

作　　者：华振兴[1] 谢红胜[1] 赵勇[1] 吴相林[1] 

机构地区：[1]华中科技大学系统工程研究所,湖北武汉430074

出　　处：《武汉理工大学学报（信息与管理工程版）》2006年第12期49-52,75,共5页Journal of Wuhan University of Technology：Information & Management Engineering

摘　　要：蚁群算法是根据真实蚁群的觅食原理提出的一种新兴的启发式搜索算法。算法应用于解决组合优化问题,取得了良好的效果。定义了一种新的旅行商问题,即过程旅行商问题,针对这个问题提出了一种基于边缘搜索的改进蚁群算法。该算法通过限制蚂蚁的起点城市,提高了蚁群算法的搜索效率;并通过减少蚂蚁数量加快计算速度。应用于过程旅行商问题的仿真计算表明,该算法具有相同的计算结果和更快的求解速率。Ant colony optimization （ACO） is a new heuristic searching algorithm, which is inspired by the foraging behavior of the real ant colonies. ACO is used to solve combination optimization （CO） problems and gets a good effect. This paper presents a new kind of traveling s.,desman problem which is called course traveling salesman problem, and gives an improved edge - searching - based ACO. The edge - searching - based ACO can enhance the searching efficiency by limiting the ants starting searching from the edge cities and speedup the calculating by reducing the number of ants. A simulation of course traveling salesman problem shows that the improved algorithm gets a same result, but a faster calculating speed.

关 键 词：蚁群算法 蚁群系统 旅行商问题 过程旅行商问题 边缘搜索 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]