摘要
结合粒子群算法、蚁群算法、重力搜索算法提出了一种新的混合算法——TSP-GPAA.该算法将粒子群算法和重力搜索算法加入到蚁群算法中,利用粒子群算法的全局搜索能力解决了蚁群算法的初始信息素匮乏的问题,并且重力搜索算法将粒子群算法和蚁群算法参数进行优化,明显提高了蚁群算法的优化性能.实验表明新算法对于解决TSP问题是有效的.
The TSP problem is very important because of its theoretical and practical significance.In this paper,a computationally effective algorithm of combining ACO,PSO and GSA is proposed for solving the TSP problem.In this algorthm,PSO and GSA have been added to ACO.The PSO algorithm solved the shortage problem of the initial pheromone towards ACO.The GSA has been used to choose the Parameters of PSO and ACO.Experimental results show that the proposed algorithm for solving the TSP problem is effective and efficient.
出处
《东北师大学报（自然科学版）》
CAS
CSCD
北大核心
2011年第3期60-64,共5页
Journal of Northeast Normal University(Natural Science Edition)
基金
国家自然科学基金资助项目(61070084
60573067
60803102)
关键词
蚁群算法
粒子群算法
重力搜索算法
旅行商问题
ant colony algorithm
particle swarm optimization
gravitation search algorithm
TSP
