Modeling and Simulation on Electric Vehicle Routing Problem with Improved Charging Strategy

Abstract

目前电动车辆路径问题中的充电策略通常是完全充电策略，会带来充电时间不灵活，难以满足客户时间窗等问题。针对该问题，提出了改进充电策略，将车辆充电时间点、充电站点和充电电量作为决策变量，以电动车辆运营总成本最小为目标函数，建立了混合整数规划模型，并提出了自适应遗传算法融合模拟退火算法的混合启发式求解算法。最后，算例仿真测试和灵敏度分析结果验证了模型和算法的有效性和实用性。The charging strategy in the electric vehicle routing problem at present is usually full charge, which will bring about the problems that the charging time is too inflexibility and the customer’s time windows are hard to be met. Therefore, an improved charging strategy is proposed, in which, the vehicle charging time, the charging station and the charging power are taken as decision variables. With the objective of minimizing the total operation costs, a mixed integer linear programming model is established. Then, a hybrid heuristic algorithm based on the combination of self-adaptive genetic algorithm and simulated annealing algorithm is proposed. Finally, the validity and practicability of the model and the algorithm are proved by a large number of computational examples and sensitivity analyses.