中文摘要：

本文通过对蚁群优化算法进行分析,提出影响蚁群优化算法收敛性、解质量和算法稳定性的几个关键问题是：下一个结点的选择、局部信息素更新的必要性和参数的选择。文中采用不同的方法解决这三个关键问题并且将算法应用到TSPs,实验结果与几个改进算法相比具有一定的优越性。本文进一步在蚁群优化算法中嵌入局部搜索方法,通过实验说明,算法的求解速度和最优解的质量都得到明显改善,算法的稳定性也明显提高。

英文摘要：

By analyzing Ant Colony Optimization Algorithm, we propose several key factors which influence the convergence, quality of solutions and stability of the algorithm. They are selection of next node, necessity of local pheromone updating, parameter settings and the number of ants. We use different ways to solve the three problems and apply the algorithm to TSPs. The results of experiments have superiority comparing with some improved algorithms. We further imbed Local Search to algorithm and find that the speed of con- vergence, quality of solutions and the stability of the algorithm are improved obviously.