基于联合配送的城市物流配送路径优化

针对城市多区域协同发展造成的商业中心相对分散的现状, 提出“多对多” 的城市网络化联合配送机制. 以运输距离、实载率等与成本密切相关的油耗成本为优化目标, 建立面向城市多区域配送需求的车辆路径模型; 同时,利用量子比特位设计染色体结构, 利用云模型云滴随机性与稳定性改进遗传算子, 设计云量子遗传算法对所建立的联合配送模型进行求解. 最后, 结合不同算例对模型和算法进行了仿真实验分析.

Route optimization of urban logistics in joint distribution

For the dispersive situation of business centers in cities caused by regional developing, networked many-tomany distribution mechanisms is proposed. And the vehicle routing optimization model for regional distributing in cities is established, taking the fuel consumption as the optimal target which is closely related to shipment distance, actual load rate and so forth. Then the cloud quantum genetic algorithm, with chromosome structure designed by utilizing quantum bits and genetic operator improved by adopting randomness and stability of cloud droplet in the cloud model, is designed to solve the routing optimization model for joint distribution. For the comparison, several different cases are conducted to illustrate the established model and solving algorithm.