求解旅行Agent问题的自适应蚁群算法

针对现有的蚁群算法在求解旅行Agent问题中所存在的全局最优解的收敛速度不强和一致性欠佳等问题，在蚁群算法的基础上，利用算法的迭代次数来动态自适应地修改选择路径上的信息素的更新规则和信息素的挥发系数，从而使Agent在路径选择中这两方面的能力得到了提高。实验结果表明，相比现有的解决旅行Agent问题的蚁群算法，该算法在求解全局最优解的收敛速度和一致性方面具有更强的优势。

Adaptive ant colony algorithm for traveling Agent problem

In view of the existing ant colony algorithm,this is not strong in the convergence rate and consistence of the global optimal solution for Traveling Agent Problem.By using the number of iterative algorithms to update the rules and information-volatile factor,the Agent can enhance the ability of choosing the path.Compared to the existing ant colony algorithm for Traveling Agent Problem,the result shows that the algorithm proposed in this paper is strong in the convergence rate and consistence of the global optimal solution.