Logistics Pure Electric Vehicle Routing Based on GA-PSO Algorithm

Abstract

Abstract:Based on current energy storage technologies such as batteries and fuel cells, the inherent battery capacity of electric vehicles puts constraints on their driving range and requires charging in the process of completing driving tasks. In this paper, with the current practical application in logistics industry as the background, from electric vehicle charging scheduling and path planning, a hybrid algorithm combining genetic-particle swarm algorithm is proposed to plan the best driving route for a group of electric logistics vehicles with vehicle load, vehicle battery life, charging facility location and customer time window as constraints and the total cost as the objective function. Based on the single distribution center, a more complex multi-distribution center electric vehicle path planning problem is considered. In this paper, multiple sets of Solomon VRPTW data sets are selected to test the prepared algorithm, and the results show that the algorithm can effectively plan the best distribution scheme.

Application of Improved Ant Colony Algorithm in Optimizing the Charging Path of Electric Vehicles

“…Therefore, improving their endurance is the focus of current research [2]. However, most of the current research only analyzes their battery conversion efficiency and charging pile construction layout, with little research on the charging selection behavior and scheduling of traditional EV users [3]. Moreover, some of these studies overlook various constraints and limitations in their actual travel process.…”