基于蚁群算法的混合优化算法在TSP中的应用  

Hybrid Intelligence Algorithm Based on Ant Colony Swarm and Its Application in TSP

作　　者：李澄非[1] 朱群雄[1] 

机构地区：[1]北京化工大学信息科学与技术学院,北京100029

出　　处：《青岛大学学报（自然科学版）》2007年第1期58-62,共5页Journal of Qingdao University(Natural Science Edition)

基　　金：教育部科学技术研究重点项目(01024)

摘　　要：针对蚁群算法收敛慢,易陷入局部最优的问题,提出了基于蚁群算法混合优化算法。该方法将传统蚁群算法中的启发式因子α,β作为每只蚂蚁的属性,利用遗传算法对蚂蚁的种群进行自然选择,优胜劣汰,优秀蚂蚁被保留并产生后代,蚂蚁的启发式因子在求解问题的动态过程中收敛到合理的范围内。将改进的算法应用于旅行商问题,实验结果表明,利用这一方法可使解的性能有所改进,并有效地减少了计算时间。Hybrid intelligence technique based on ant colony swarm is introduced in order to adjust ant colony algorithm parameters. The key parameters are taken as the attributes of ant instead of constant. The best ant individual is saved while the worst ant individual is abandoned via genetic operator. Parameter adaptation dynamically occurs in parallel to the running of the hybrid algorithm. The proposed algorithm is compared with the algorithms that use standard parameter sets. Experimental results in traveling salesman problem （TSP） show that the improved algorithm offers two advantages of the time of finding the optimal solution and the performance of the optimal solution.

关 键 词：蚁群算法 遗传算法 启发式因子 旅行商 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] TP18[自动化与计算机技术—计算机科学与技术]