求解TSP问题的增强型自探索粒子群算法  

Enhanced self-tentative particle swarm optimization algorithm for TSP

作　　者：熊伟[1] 张江维[2] 张火林[2] 

机构地区：[1]华北电力大学控制科学与工程学院,河北保定071003 [2]许昌学院计算机科学与技术学院,河南许昌461000

出　　处：《华北电力大学学报（自然科学版）》2009年第6期69-74,85,共7页Journal of North China Electric Power University：Natural Science Edition

基　　金：河南省教育厅基础研究资助项目(2008B520032)

摘　　要：分析了单点调整思想自探索粒子群算法求解TSP问题的不足,并以此为基础构造了求解TSP问题的增强型自探索粒子群算法。在算法中进一步强化了粒子的自探索行为,增加了随机序列段调整思想,以提高算法发现全局最优解的概率。实验结果分析,表明了该增强型自探索粒子群算法具有较强的全局搜优能力,比其他同类算法获得了质量更高的解。The limits of the single- node adjustment self- tentative particle swami optimization algorithm （PSO） was analyzed in this paper, and on the basis of which an enhanced self- tentative particle swarm optimization algorithm （ESTPSO） has been proposed for the TSP problems. In order to improve the performance of the algorithm, the idea of random sequence adjustment has been added in the algorithm. Experimental results show that the ESTPSO algorithm can achieve better solutions than other approaches, and has the better ability for finding the global optimum.

关 键 词：TSP 粒子群算法 增强型自探索粒子群算法 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]