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

Abstract

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.