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Optimization Research on Vehicle Scheduling Path for Emergency Repairs of Power Transmission Lines

机译:输电线路抢修车辆调度路径的优化研究

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Optimization research on vehicle scheduling path for emergency repairs of power transmission lines is the problem how the repair vehicles can quickly reach the repair scene along the optimal path, is the problem of finding the optimal path. In this paper, a method of dynamically dividing the search area is proposed in order to narrow the search range and improve the search speed. At the same time, in view of the shortcomings that the road network topology map can't use the real-time traffic information as the weight, this paper adopts the genetic-improved Max-Min Ant System (MMAS) algorithm. Using the average waiting time of road sections in different time periods as an integral part of visibility calculation, the optimal combination of the five control parameters is obtained by using the genetic-modified MMAS algorithm, then using this combination to guide the improved MMAS algorithm to find the optimal path. Simulation results show that this method has more advantages than other methods in solving the optimal repair path of power line.
机译:输电线路抢修车辆调度路径的优化研究是抢修车辆如​​何沿最优路径快速到达维修现场的问题,是寻找最优路径的问题。为了缩小搜索范围,提高搜索速度,提出了一种动态划分搜索区域的方法。同时,针对道路网络拓扑图不能利用实时交通信息作为权重的缺点,本文采用遗传改进的Max-Min Ant System(MMAS)算法。将不同时间段路段的平均等待时间作为能见度计算的组成部分,使用遗传改进的MMAS算法获得五个控制参数的最佳组合,然后用该组合指导改进的MMAS算法进行计算。找到最佳路径。仿真结果表明,该方法在解决电力线最优修复路径方面比其他方法更具优势。

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