跨境电商BC业务运单分配及路线优化策略  

Waybill Allocation and Route Optimization Strategy for Cross-border E-commerce BC Business

作　　者：冯华[1] 徐晗 李建斌[2] 梅启煌 FENG Hua;XU Han;LI Jianbin;MEI Qihuang(School of Economics and Management,Wuhan University,Wuhan 430072,China;School of Management,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]武汉大学经济与管理学院,湖北武汉430072 [2]华中科技大学管理学院,湖北武汉430074

出　　处：《工业工程与管理》2022年第6期32-40,共9页Industrial Engineering and Management

基　　金：国家自然科学基金重点项目(71831007);国家自然科学基金面上项目(72071085)。

摘　　要：通关是跨境物流运输的重要环节之一,由于通关监管点的通关制度不同导致商品的通关时间存在差异,极大地影响配送时间,因此将各运单内的商品分配到合适的监管点,并选取合理的通关路线尤为重要。通过分析跨境电商第三方物流企业BC直购进口业务中运单内商品的通关过程,考虑通关效率和海关配额两个因素,以最小化通关时间及成本为目标,建立双目标0-1整数规划模型。设计双目标粒子群算法进行求解。算例结果表明,所设计算法求得的通关及运输方案比企业实际业务方案通关时间减少51.05%,通关成本降低52.60%,同时其在求解效率、解的质量等方面与常见的NSGA-II、MOEA/D算法相比均具有明显优势。One of the most important processes of the cross-border logistics is the customs clearance.Due to different clearance systems of clearance supervision points,there are differences in the clearance time of different commodities,which greatly affects the delivery time. Therefore,it is particularly important to allocate the goods in the waybills to appropriate clearance supervision points and select reasonable customs clearance routes. By analyzing the process of clearance,clearance efficiency and customs quotas were considered to establish a dual goal 0-1 integer model with the goal of minimizing customs clearance time and costs. A dual-objective particle swarm algorithm was designed to solve this model. The results show that the optimal clearance and transportation solution obtained by the dual-objective particle swarm algorithm could reduce the customs clearance time by 51.05% and the customs clearance cost by 52.60% averagely compared with the current situation of the enterprise. Moreover,compared with NSGA-Ⅱ and MOEA/D algorithms,it has obvious advantages in solving efficiency and solution quality.

关 键 词：跨境电商 直购进口 通关效率 运单分配 

分 类 号：U4[交通运输工程—道路与铁道工程] TP39[自动化与计算机技术—计算机应用技术]