服务差异二级选址路径问题及大邻域搜索算法

Adaptive Large Neighborhood Search Algorithm for Two-Echelon Location-Routing Problem with Different Service Modes

在电子商务背景下,物流公司为了实现及时交付并缓解交通拥堵,可按照客户不同的服务需求,将其分为自取型和配送型,进而选择开放自助点或配送点对客户进行服务。自助点和配送点作为二级物流设施,配送中心作为一级物流设施,由此形成了二级选址-路径问题。在配送车数量约束、自助点容量约束等限制下,兼顾客户点物品回收,以总物流成本最小为目标,建立考虑服务差异的二级选址-路径问题模型。设计自适应大邻域搜索算法进行求解,通过Nguyen的2E-LRP算例进行测试,更新了1个算例的全球最优解,其余算例达到或接近最优解,平均Gap值在1.22%以内,验证了算法的有效性及良好的收敛性。实际案例模拟分析验证了模型的有效性和适用性,可以为相关物流企业提供决策依据和参考。

With the growing popularity of e-commerce, in order to achieve faster delivery and reduce inner-city traffic congestion, one alternative approach is to divide customers into self-service and distribution service according to customers’ different needs, and then some self-service points or satellites are chosen to serve customers. The self-service points and satellites are the secondary logistics facilities, and the distribution center is the first-level logistics facility, which forms a two-echelon location-routing problem. In order to minimize the total logistics cost, a two-echelon location-routing problem with different service modes model is established, considering the constraints like the number of distribution vehicles and the capacity of self-service points. Then, an adaptive large neighborhood search(ALNS)algorithm is designed to solve the proposed model. Tested by Nguyen’s 2E-LRP instances, the best known solution of one instance is updated by the ALNS, and the other instances reach or close to the best known solution, and the average gap value is within1.22%, and the effectiveness and good convergence of the algorithm are verified. Finally, based on simulation data, the model is proved to be valid and applicable. This study can provide decision support for relevant logistics enterprises.