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

机译:电力传输线应急维修车辆调度路径优化研究

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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:电力传输线应急维修车辆调度路径的优化研究是如何沿着最佳路径快速到达修复场景的问题的问题,是找到最佳路径的问题。在本文中,提出了一种动态划分搜索区域的方法,以缩小搜索范围并提高搜索速度。同时,鉴于道路网拓扑图无法使用实时交通信息作为重量的缺点,本文采用遗传改进的MAX-MIN蚁系统(MMS)算法。在不同时间段中使用路段的平均等待时间作为可见性计算的组成部分,通过使用遗传修改的MMA算法来获得五个控制参数的最佳组合,然后使用该组合来引导改进的MMA算法找到最佳路径。仿真结果表明,该方法具有比解决电力线最佳修复路径的其他方法的优点。

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