The basic principle of Ant Colony algorithm and main parameters about this algorithm are determined are described. These parameters which greatly influence the ant colony algorithm' capacity of searching optimal so-lution comprise the inspired factor (e), the expectation inspired factor β, ant population m, information strength Q and the pheromone volatilization factor ρ. Employing the Travelling Salesman problem (TSP) as an example, dif-ferent combined conditions about these parameters are studied. Firstly, according to the result of numerical exam-ples, selects [(e),β,m,Q,ρ] =[1.5, 4.2, 30,200,0.5], Secondly, 4 parameters of them, Conducts numerical experiments by changing the remaining parameter value are fixed. Through getting (e) ∈ [0. 7,1.1],β ∈ [3.8, 4. 5] ,Q ∈ [400,950] and ρ ∈ [0. 7,0. 9] , the stable global optimal solution could be achieved.%介绍了蚁群算法的基本原理.确定了蚁群算法中的主要参数,这些参数对蚁群算法的寻优能力的影响非常之大,有启发因子δ,期望启发因子β,蚁群数量m,信息强度Q和信息素会发因子ρ等参数,以旅行商问题为例优化以上参数,研究这些参数的组合情况.首先根据数值试验选定[δ,β,m,Q,p]=[1.5,4.2,30,200,0.5].固定四个参数,改变一个参数进行数值试验.得到δ∈ [0.7,1.1],β∈[3.8,4.5],Q∈ [400,950]和p∈[0.7,0.9]能得到稳定的全局最优解.
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