电动汽车共享站点间车辆人工调度策略

InterSiteVehicle Artificial Scheduling Strategy Design for Electric Vehicle Sharing

摘要:

用户出行需求的潮汐性和不均衡性导致站点间车辆失衡问题严重，极大地制约了电动汽车共享的快速发展，采用合理的车辆人工调度策略可使车辆失衡问题得以解决.基于完全满足用户用车需求的前提，建立成本最低的调度需求模型，并采用遗传算法求解得出调度需求.构建了电动汽车共享站点间车辆人工调度策略，同时通过调度收益最大化的混合整数规划模型优化车辆调度路径，采用分支定界法求解.以“EVCARD”位于上海市嘉定区5个站点的实际订单作为输入，进行人工调度策略优化分析.结果显示：在用户用车需求增长的情景下，不增设停车位和车辆数目而采用人工调度优化策略，同比可以提升60%的订单服务量，相比增设停车位和车辆数目可以节约60%的成本投入.

Abstract:

The intersitevehicle imbalance is a major puzzle which has seriously hindered the development of electric vehiclesharing. A set of reasonable vehicle scheduling scheme can solve this puzzle. Firstly, the minimum cost of scheduling demands model based on satisfying all the consumers’ demands was constructed with the genetic algorithm to solve the model. Secondly, after obtaining scheduling demands, a mixed integer programming model was proposed to optimize the dispatchers’ routes, and the branch and bound algorithm was used to solve the model. Finally, taking orders data of five specified sites as input for a case calculation. The calculation results indicate that in the situation of increased demand, if artificial scheduling strategy is adopted, the ability to accept orders can be increased by 60%. In addition, it can save 60% of the cost input comparing with increasing the number of parking spaces and vehicles.