针对基本蚁群算法 ,设计出一种新颖的随机扰动蚁群算法 ,并将其应用于求解复杂 TSP问题 .该算法包含了两个重要方面 :一是提出了采用倒指数曲线来描述的扰动因子 ;二是设计出了相应的随机选择策略和扰动策略 .数值模拟表明 :该算法可以有效地克服基本蚁群算法的计算时间较长和容易出现停滞现象的缺陷 ,具有更好的全局搜索能力 .此外 ,还对该算法中参数的取值范围及选取方法进行了研究和探讨 Aiming at the basic ant colony algorithm, a novel stochastic perturbation ant colony algorithm is designed and applied to solving complex TSP problems.This algorithm contains two important aspects: First, it proposes the use of inverse exponential curve to describe the disturbance factor The second is to design a corresponding random selection strategy and disturbance strategy.The numerical simulation shows that this algorithm can effectively overcome the shortcomings of the basic ant colony algorithm calculation time is long and easy to stagnate, with better global search ability. In addition, the range of the parameters in the algorithm and the selection method are also studied and discussed