Workshop’s Topic: We examine an online retailer that sells multiple products across different zones over a finite time horizon with multiple periods. The goal is to maximize the retailers expected profit during this period. In the single-zone scenario, we demonstrate that the multi-period problem can be reduced to a single-period problem. In this case, the optimal retrieval decisions follow a greedy policy, which suggests retrieving products from the warehouse with the lowest cost. Additionally, we develop a non-greedy algorithm to identify the optimal storage policy and analytically characterize the best ordering policy. However, the multi-zone scenario is analytically intractable, so we propose an efficient heuristic to address this complexity. This heuristic is a sophisticated combination of three different approximations. Our numerical experiments indicate that this hybrid approach outperforms two conventional benchmarks by as much as 22.5% and 3.5%, depending on various factors such as horizon lengths, fulfillment frequencies, warehouse capacities, demand variations, and demand correlations.

Time and Location: 10:00 AM (GMT+8), Room A823 (School of Management)

Language: Bilingual (Chinese and English)