This essay puts forward an improved ant colony algorithm based on the introduction of the variability of non-uniform mutation operator. It makes the path optimization, which uses optimized ant colony algorithm to complete the task of ant colony after the completion of one iteration and non-uniform mutation operator mutation. It can speed up the convergence of the algorithm. The satisfactory results are reached after N evolutions. Simulation results demonstrate that the optimal solution and stability of the improved algorithm are better than the basic ant algorithm and Ant Colony Optimization(ACO) algorithm.%为解决对称旅行商问题,在改进蚁群优化算法的基础上,提出一种引入非均匀变异算子的改进算法。在路径寻优时采用改进的蚁群优化算法,且在完成一次循环迭代后,运用非均匀变异算子对已完成该次任务的蚁群进行变异处理,从而加快算法收敛速度,经过N次进化直至达到满意结果。仿真结果表明,在寻最优解的能力和算法稳定性方面,该算法比基本蚁群算法和蚁群优化算法更强。
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