摘要
笔者以求解旅行商问题的最短巡回路径为主要研究对象,对蚁群算法和遗传算法以及二者融合后的原理进行说明。在此基础上建立了它们的数学模型,并详细分析了其求解旅行商问题的步骤。通过对比分析三种算法在eil101算例上的寻优结果可知,在此算例规模的TSP问题上,蚁群算法与遗传算法融合后的寻优效果,明显好于两种算法单独运算时的求解效果。
In this paper,the shortest path of traveling salesman problem is taken as the main research object,and the principles of ant colony algorithm and genetic algorithm and their fusion are explained.On this basis,their mathematical models are established and their steps to solve the traveling salesman problem are analyzed in detail.By comparing and analyzing the optimization results of three algorithms in the case of eil101,it can be seen that the optimization effect of ant colony algorithm and genetic algorithm is better than that of the two algorithms when they are operated separately on the TSP problem of the scale of the example.
作者
蒋晓继
Jiang Xiaoji(Liaoning Normal University Haihua College,Shenyang Liaoning 110000,China)
出处
《信息与电脑》
2019年第3期56-59,62,共5页
Information & Computer
关键词
蚁群算法
遗传算法
融合
TSP
ant colony algorithm
genetic algorithm
fusion
TSP
