带硬时间窗的冷链电动车辆路径问题研究

Research on Electric Vehicle Routing Problem with Time Windows for Cold Chain

[目的]针对电动汽车应用于冷链物流配送的情形,充分考虑电动汽车能耗特点和社会充电桩的充电需求,研究了带硬时间窗的冷链电动车辆路径问题。[方法]首先构建以配送总成本最少为优化目标的规划模型;然后基于蚁群算法,设计了充电站优化算法和局部优化策略,形成混合蚁群算法求解问题;最后,改编形成硬时间窗冷链电动车辆路径问题的算例集,通过实验比较验证了蚁群算法和混合算法的性能。[结果]搜索解的改进率达到11.82%。[结论]带局部优化策略的混合蚁群算法能较大程度改进求解能力,算法性能总体得到大幅提升,且结果更稳定。

[Purposes]In view of the situation of cold chain logistics distribution of electric vehicles,fully considering the characteristics of electric vehicles and the charging needs of social charging piles,the cold chain electric vehicle routing problem with hard time window(EVPRHTW-CC)is studied.[Methods]First,a planning model with the minimum distribution cost as the optimization goal is constructed.Then based on the ant colony algorithm,a kind of charging station optimization algorithm and local optimization strategy are designed to form a hybrid ant colony algorithm conversion problem.Finally,a set of examples of the hard time window cold chain electric vehicle routing problem are adapted and the performance of the ant colony algorithm and the hybrid algorithm is verified through experiments.[Findings]The improvement rate of the search solution reaches 11.82%.[Conclusions]The results show that the hybrid ant colony algorithm with local optimization strategy can greatly improve the solution ability,the overall performance of the algorithm is greatly improved,and the solution is more stable.