讲座主题：Joint Initial Stocking and Inventory Transshipment for Multi-Location Problems

讲座时间：2025年4月21日（周一） 10:00-11:30

讲座地点：经济管理学院B220

报告人：Sean Zhou（周翔 教授）

邀请人：胡祥培 教授

报告人简介：

Sean Zhou is Professor and Chair of Department of Decisions, Operations and Technology, CUHK Business School, and Professor in Department of Systems Engineering and Engineering Management (by courtesy), at The Chinese University of Hong Kong (CUHK). He has held visiting positions at National University of Singapore and University of Toronto. He received his PhD in Operations Research from North Carolina State University. His main research interests are inventory management, pricing, sustainable operations, data-driven supply chain optimization, and operations and marketing interface. He serves as Area Editor (Inventory and Supply Chain Optimization) of OR Letters and Associate Editors of various journals including Naval Research Logistics and Service Science.

讲座简介：

We study initial stocking and inventory transshipment for a firm selling its product via multiple outlets/stores. At the beginning of the selling season, the firm needs to distribute product inventory to the outlets (initial stocking), which, in turn, supply customer demands. Customer demand to each store follows independent compound Poisson processes. Over the selling season, when needed, a re-distribution or transshipment of inventory can be carried out between the outlets. The firm aims to maximize the total expected profit over the season. We first employ stochastic dynamic programming (DP) to formulate the problem and characterize the optimal transshipment policy for a three-location problem. The optimal transshipment policy is already quite complex and determined by sets of constants and functions (depending on the inventory status of stores) each period. In view of the challenge of using DP to solve the general multi-location problem, we design a simple heuristic policy that utilizes the solutions of easily solvable deterministic problems. By benchmarking against an upper bound problem, we show that the heuristic has a constant loss relative to the optimal profit, independent of the length of the selling season. We also develop an algorithm with a performance guarantee for computing the initial stocking levels used in the heuristic. Finally, a numerical study with model parameters calibrated by real data from a medical device distributor demonstrates the effectiveness of the heuristic. This is joint work with David Yao (Columbia Univ.), Zhuoluo Zhang and Weifen Zhuang (both at Xiamen Univ.).