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中国管理科学 ›› 2023, Vol. 31 ›› Issue (2): 205-214.doi: 10.16381/j.cnki.issn1003-207x.2020.0768

• 论文 • 上一篇    下一篇

基于PI的企业动态库存补货模型与算法

戢守峰, 刘红玉, 赵鹏云, 戢婷婷   

  1. 东北大学工商管理学院,辽宁 沈阳110004
  • 收稿日期:2020-04-28 修回日期:2022-12-29 出版日期:2023-02-20 发布日期:2023-02-28
  • 通讯作者: 刘红玉(1994-),女(汉族),河北秦皇岛人,东北大学工商管理学院,博士研究生,研究方向:物流系统建模与优化、物流与供应链管理,Email:liuhongyu@stumail.neu.edu.cn. E-mail:liuhongyu@stumail.neu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(71972019,71572031);高校基本科研项目(LJKMR20220343);辽宁经济社会发展立项课题(2022slybkt-029)

Model and Algorithm of Dynamic Inventory Replenishment Based on Physical Internet

JI Shou-feng, LIU Hong-yu, ZHAO Peng-yun, JI Ting-ting   

  1. School of Business Administration, Northeastern University, Shenyang 110004, China
  • Received:2020-04-28 Revised:2022-12-29 Online:2023-02-20 Published:2023-02-28
  • Contact: 刘红玉 E-mail:liuhongyu@stumail.neu.edu.cn

摘要: PI(physical internet)环境下的物流网络具有互联、开放和共享的特点,缺货的PI-枢纽或零售商可根据货源选择策略动态选择为其补货的供应商或PI-枢纽。为解决PI环境下库存补货问题,提出了IB-EB(installation-echelon)混合补货策略。以最小化库存补货成本为目标,补货量和再订购点为决策变量,构建了PI环境下的动态库存补货模型。针对该混合整数非线性规划模型,应用粒子群优化算法求解出多个补货预案,再将其带入仿真环境循环优化求解。最后,以中国航空器材进出口公司为例,验证了模型可解性及算法的可行性。结果表明PI环境下货源策略的选择对库存补货成本和补货策略具有十分重要的影响,为企业在不同补货条件下选择货源提供了参考依据。

关键词: PI;动态IB-EB混合补货策略;混合整数非线性规划;粒子群-仿真优化算法

Abstract: With the advent of an era of intelligence and information, it is so difficult for current logistics network to meet increasingly various customer demand. For improving the inventory replenishment level of enterprises, the concept of Physical Internet is introduced. Different from traditional logistics network, the logistics network of Physical Internet has characteristics of interconnection, openness and sharing. According to source selection strategy, the suppliers or PI-hubs can be selected by the stockout PI-hubs or retailers dynamically. In order to solve the problem of inventory replenishment in Physical Internet, a hybrid replenishment strategy of Installation-Echelon is proposed. Besides, the dynamic inventory replenishment model is constructed in Physical Internet. The objective function is represented by minimizing inventory replenishment cost and the decision variables are expressed by replenishment quantities and reorder points. Aiming to solving the large-scale dynamic mixed integer nonlinear programming model, several replenishment predetermined plans are obtained by particle swarm optimization algorithm. Then predetermined plans are circularly brought into the simulation environment to optimize. Finally, taking the China Aviation Equipment Import and Export Corporation as an example, the solvability of the model and the feasibility of the algorithm are verified. The results show that source selection strategy in Physical Internet has a significant impact on replenishment cost and replenishment strategy, which provides a reference value for enterprises to formulate inventory replenishment strategy and select source under different conditions.

Key words: Physical Internet; dynamic installation-echelon hybrid replenishment strategy; mixed integer nonlinear programming; particle swarm-simulation optimization algorithm

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