基于方向信息素协调的蚁群算法

Ant algorithm based on direction-coordinating

为了克服传统蚁群算法易出现的停滞现象,定义一种新的方向信息素来刻画寻优过程中的全局信息,从而保证在最优路径的基础上提高解的全局性,并加快算法的收敛;此外,由于新的探索率因子的提出及全局选择策略的修正,使得信息素较弱的路径得以选择,进而扩大了搜索的范围,提高了算法的鲁棒性.最后,通过多个不同规模旅行商问题的测试,与蚁群系统算法相比,实验结果表明了该算法具有更好的搜索能力及更快的收敛速度.

To overcome the stagnation of the search in classical ant colony algorithms, the paper defines a new directed pheromone to represent the global information of searching. Accordingly, the global searching ability and the convergence speed of the proposed algorithm are enhanced. Furthermore, the probability of premature convergence is low due to the introduction of the new explore-rate parameter and the modification of global chosen rule, which can increase the probability of selecting the arcs with low pheromone trail. Finally, the improved algorithm and the ant colony system（ACS） algorithm are used in several different travelling salesman problems（TSP） for comparing experiments. The results show that the proposed algorithm has more accurate searching results and faster convergence speed.