主管：中国科学院
主办：中国优选法统筹法与经济数学研究会
　　　中国科学院科技战略咨询研究院
中国管理科学

中国管理科学 ›› 2023, Vol. 31 ›› Issue (3): 38-47.doi: 10.16381/j.cnki.issn1003-207x.2022.0379

• 论文 • 上一篇    

医药电商考虑信息动态更新和最小化拆单率的订单重分配优化研究

李建斌1, 王莹莹1, 李明康1, 郑宇婷2   

  1. 1.华中科技大学管理学院，湖北 武汉430074；2.福州大学经济与管理学院，福建 福州350108
  • 收稿日期:2022-02-27 修回日期:2022-09-06 发布日期:2023-04-03
  • 通讯作者: 郑宇婷(1992-)，女(汉族)，福建福州人，福州大学经济与管理学院,副教授，博士，硕士生导师，研究方向：电子商务、运作管理、物流与供应链管理，Email:ytzheng@fzu.edu.cn. E-mail:ytzheng@fzu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(71831007，72071085)；华中科技大学人文社科培育项目(2021WKFZZX008)

Research on Order Reallocation Optimization of Pharmaceutical E-commerce Considering Dynamic Update of Information and Minimizing Order Splitting Rate

LI Jian-bin1, WANG Ying-ying1, LI Ming-kang1, ZHENG Yu-ting2   

  1. 1. School of Management, Huazhong University of Science and Technology, Wuhan 430074, China;2. School of Economics and Management, Fuzhou University, Fuzhou 350108, China
  • Received:2022-02-27 Revised:2022-09-06 Published:2023-04-03
  • Contact: 郑宇婷 E-mail:ytzheng@fzu.edu.cn

PDF (PC)

388

摘要： 随着“互联网+医疗健康”的普及，小型医疗机构通过与医药电商的合作，多频次小批量地向医药电商采购药品，以降低自身库存成本。医药电商为保证医药品配送时效性，极易出现订单拆分现象，这不仅使得电商企业物流环节的配送成本大幅增加，也降低了用户满意度。为提升医药电商物流效率，满足药品即时配送的需求，本文建立了医药电商订单动态分配模型，在考虑库存信息动态更新的同时，也考虑了订单信息更新重分配优化策略。设计库存信息动态更新(DIIO)算法与信息更新双重优化(DIDO)算法，前者降低医药电商拆单率29.45%，后者通过订单重分配降低仓库出货次数50.41%，每月节约配送成本约115.41万元。在缓解小型医疗机构的库存压力的同时，也提升了医药电商的物流效率，达到多方共赢的目的。

关键词: 拆单率；订单重分配；信息更新；医药电商

Abstract: With the popularity of “Internet+healthcare”, small medical institutions cooperate with pharmaceutical e-commerce to purchase medicines in small batches frequently to reduce their own inventory costs. In order to ensure the timeliness of medicine delivery, order splitting can easily happen in pharmaceutical e-commerce, which not only increases the distribution cost of logistics of e-commerce enterprises, but also reduces customer satisfaction. In order to improve the logistics efficiency of pharmaceutical e-commerce and meet the demand of instant medicine delivery, a dynamic order distribution model of pharmaceutical e-commerce is established, which not only considered the dynamic update of inventory information, but also considered the optimization strategy of order information update and reallocation. The dynamic update of inventory information (DIIO) algorithm isdesigned and dual optimization of information update (DIDO) algorithm is designed to divide the dynamic problem in the planning cycle into multiple static sub-problems. First, the greedy algorithm is used to generate the initial solution, and then the integer programming model is used to get the optimal solution. In the process of constructing the initial solution, through order classification, the SKU demand of a single order is converted into inventory, which greatly improves the optimization space of multi-order allocation. Secondly, by recursively traversing the optimal allocation results of multiple orders, an accurate solution is obtained with high efficiency. Based on the analysis of the data of a pharmaceutical e-commerce B2B platform, the DIIO algorithm reduces the order splitting rate of pharmaceutical e-commerce by 29.45%, while the latter reduces the number of warehouse shipments by 50.41% through order reallocation, saving about 1.1541 million yuan in monthly distribution cost. In addition, through the sensitivity analysis of parameters such as the per capita order frequency and the number of SKUs in the order, both algorithms have good robustness. It not only alleviates the inventory pressure of small medical institutions, but also improves the logistics efficiency of pharmaceutical e-commerce, so as to achieve the goal of win-win.

Key words: order splitting rate; order reallocation; information update; pharmaceutical e-commerce

中图分类号: