基于改进的最大最小蚁群算法求解电力线路最佳抢修路径

电力线路最佳抢修路径就是一条物资点到故障点耗费时间最少的交通路径。最大最小蚁群算法改善了基本蚁群算法的过早停滞现象，适合于求解大规模问题，但仍存在收敛速度慢、求解质量差等缺点。针对最大最小蚁群算法的不足，提出了一种改进的最大最小蚁群算法来求解电力线路最佳抢修路径。该算法采用分段函数设置状态转移规则，结合噪声扰动方法进行局部搜索，并利用变异思想和A*算法产生邻域解。仿真实验表明，在求解电力线路最佳抢修路径时，该算法比其他改进蚁群算法具有更多的优越性，并分析了噪声扰动方法的参数对求解质量的影响。

Searching optimal rush repair path of power lines based on improved max-min ant colony algorithm

The optimal rush repair path of power lines is a traffic road which costs the least time from the location of materials to location of fault. The max-min ant colony algorithm improved the premature stagnation brought by the basic ant colony algorithm, is suitable for solving large-scale problem. However, it still had some shortcomings such as slowly convergence rate and the poor quality of results. Based on the shortcoming of the max-min ant colony algorithm, this paper proposed an improved max-min ant colony algorithm to solve the optimal rush repair path. Segmented function for choosing state transition rule was introduced in the improved algorithm, as well as noising method for local search and the variation thought and A* algorithm for generating the neighborhood of the current solution. The simulation tests prove that the improved max-min ant colony is superior to any other improved ant colony algorithm in solving the optimal rush repair path of power lines, and analyze the impact of parameters in noising method on quality of solution.