Optimal Policies for a Multi-Echelon Inventory Problem with Service Time Target and Expediting
研究了多级供应链中在固定服务时间目标下的最优订购、加急和分配策略，用动态规划刻画最优策略并开发多项式时间算法，为管理者提供决策工具。
Problem definition: We study the optimal inventory ordering, expediting, and allocation decisions in a multiechelon supply chain over a finite horizon, in which customer orders are quoted with a fixed fulfillment time window, termed the service time target (STT). Academic/practical relevance: Service time target is commonly used as a marketing strategy to increase customer satisfaction and strengthen firms’ competitive edge. However, how to efficiently manage a multistage supply chain to meet the target has received relatively scant attention in the literature. Our study fills this gap. Methodology: We use dynamic programming to characterize the optimal policy. Results: We show that an echelon base stock policy and a rationing policy are optimal for inventory ordering and inventory allocation/expediting, respectively. We also develop a polynomial-time algorithm to compute the optimal policy. To derive these results, we uncover a new functional property named the decomposable of degree 2 property, which is a nontrivial generalization of the celebrated Clark-Scarf decomposition. This property further allows us to derive induced penalty and compensation to coordinate a decentralized serial system with STT and expediting. Managerial implications: Our result provides an efficient decision tool for managing centralized and decentralized serial supply chains with STT and expediting. Our model can be used to quantify the tradeoff between marketing and operational decisions, such as the impact of a marginal reduction in STT on system cost and expedition frequency, as explored in our numerical studies.