基于需求预测的两级动态配送路径优化研究

针对传统响应式配送难以应对海量动态客户需求的困境，在此提出基于需求预测的两级动态配送路径优化方法。利用历史数据从需求预测、需求聚类和需求配额三个维度，处理电商物流配送过程中的动态需求；建立基于需求预测的单阶段和多阶段两级车辆配送路径优化模型，并针对问题特性利用分支定界算法与CW-禁忌搜索算法生成两个阶段的最优配送路径。最后结合实验案例对模型与算法的有效性进行验证，试验结果表明本文设计方法具有较好的动态场景适应度和客户响应能力。

Two-echelon Dynamic Vehicle Routing Problem with Request Forecasting

E-commerce transactions have broken through the restrictions on commodity trading imposed by traditional trading channels such as time, space and region, and its platforms have attracted more and more consumers with many advantages such as abundant commodities, cheap prices, convenient payment and fast information update. However, e-commerce logistics is famous for its complexity of diversified commodities, dispersed customers, and massive dynamic demand. The links and processes of logistics distribution are very complex. Although the e-commerce platform and logistics enterprises jointly set up the logistics distribution system, tens of millions of express parcels are rushing to the end link of urban distribution in the face of holiday promotion. The lack of effective resource allocation and the last kilometer of collaborative operation of distribution cannot timely respond to the massive distribution demand at the end link.