A reinforcement learning approach for inventory replenishment in vendor-managed inventory systems with consignment inventory

In a Vendor-Managed Inventory (VMI) system, the supplier makes decisions of inventory management for the retailer; the retailer is not responsible for placing orders. There is a dearth of optimization models for replenishment strategies for VMI systems, and the industry relies on well-understood, but simple models, e.g., the newsvendor rule. In this article, we propose a methodology based on reinforcement learning, which is rooted in the Bellman equation, to determine a replenishment policy in a VMI system with consignment inventory. We also propose rules based on the newsvendor rule. Our numerical results show that our approach can outperform the newsvendor.