求解TSP的带混沌扰动的模拟退火蚁群算法  

Chaotic-simulated annealing ant colony algorithm for TSP

作　　者：王迎[1] 张立毅[2] 费腾[2] 周修飞 

机构地区：[1]天津商业大学经济学院,天津300134 [2]天津商业大学信息工程学院,天津300134

出　　处：《计算机工程与设计》2016年第4期1067-1070,1112,共5页Computer Engineering and Design

基　　金：国家自然科学基金青年基金项目(61401307);中国物流学会研究课题基金项目(2014CSLKT3-176);天津市科技特派员基金项目(15JCTPJC63000)

摘　　要：针对蚁群算法易陷入局部最优及收敛速度较慢的问题,提出一种带混沌扰动的模拟退火蚁群算法。引入模拟退火机制及混沌系统,分别对基本蚁群算法中的蚂蚁种群搜寻范围以及信息素设定与更新进行改进,提高蚁群算法全局搜索能力。使用该算法与基本蚁群算法同时求解TSP这一经典组合优化问题,对两种算法的求解性能进行对比分析。仿真结果表明,该算法的求解精度及求解效率都明显优于基本蚁群算法。Aiming at the problems of local optimization and low convergence rate of ant colony optimization,chaotic-simulated annealing ant colony algorithm was proposed.The simulated annealing method and the chaotic system were introduced to the ant colony algorithm to improve the search range of ants as well as the initialization and update of pheromone.The effectiveness of ant colony algorithm and chaotic-simulated annealing ant colony algorithm is validated by solving traveling salesman problem.Results of simulation and comparison show that the proposed algorithm is better than ant colony algorithm in both accuracy and efficiency of optimization.

关 键 词：蚁群算法 模拟退火算法 混沌扰动 旅行商问题 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]