摘要
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.
出处
《北京交通大学学报》
CAS
CSCD
北大核心
2017年第3期15-21,共7页
JOURNAL OF BEIJING JIAOTONG UNIVERSITY
基金
山东省重点研发计划(2016GGX105004)~~
关键词
电动汽车
车辆路径问题
集散货一体化
充电
electric vehicle
vehicle routing problem
delivery and pick-up
charging