摘要
通过对蚂蚁构建路径的分析，发现蚁群优化算法在求解旅行商问题（travelingsalesmanproblem，TSP）构建路径时，存在后半程的边较前半程的边质量差的缺陷。提出了动态变化的蒸发因子，减少了路径后期信息素对后续蚂蚁的影响，提高了后续蚂蚁构建路径的质量。仿真实验结果表明，该算法对解决TSP问题具有更优的全局搜索能力。
Ant colony optimization algorithm was found that the quality of the second half edges of rout was worsen than the first half edges of rout for solving TSP （traveling salesman problem） through analyzing ants＇constructing route. Based on above, dynamic evaporating factors were introduced, it reduced the influence of pheromone on subsequence ants, enhanced the subsequence ants＂ constructing quality. The simulation results show that the algorithm has better global search ability to solve the TSP.
出处
《军事交通学院学报》
2012年第9期88-91,共4页
Journal of Military Transportation University
基金
基金项目：全军科研“十二五”计划项目（11QJ003-206）
关键词
蚁群系统
动态蒸发因子
旅行商问题
信息素
ant colony system
dynamic evaporating factor
traveling salesman problem
pheromone
