电动汽车集散货一体化车辆路径问题

Electric vehicle routing problem with simultaneously delivery and pick-up

针对电动汽车特性,考虑里程约束和时间窗约束,建立以最小化总费用为目标的电动汽车集散货一体化车辆路径问题模型.模型考虑了车辆可在行驶途中多次前往充电站补充电量.因此,避免由于电量不足导致的车辆半路抛锚及电池过度放电.应用遗传算法求解模型,得到包含配送计划、行车时间及充电计划在内的配送方案.并基于Dijkstra算法求解任意两个邻接节点之间最短路径问题,在路网上为车辆规划行车路线.结合北京市城区路网的算例验证模型和方法的有效性和实用性.

Based on the characteristics of electric vehicle （EV）, this paper, taking the range con- straint and time-window constraint into consideration, develops an EV routing problem model with simultaneous delivery and pick-up, aiming to minimize the total cost. To avoid the depletion of battery power and battery over-discharge caused by insufficient battery power, EV powered by on board batteries can recharge at charging stations when travelling. Then, a genetic algorithm （GA） is applied to solve the proposed model, obtaining the distribution solution consisted of dis- tribution plan, timetable and charging plan. Moreover, the shortest path problem between any two adjacent nodes is addressed by Dijkstra algorithm so that the vehicle routes planning can be exerxised in road network. Lastly, a realistic case study on the road network in Beijing urban area is conducted to prove the proposed model and the algorithm effective and practical.