A Reinforcement Learning Approach for Inventory Replenishment in Vendor-Managed Inventory Systems With Consignment Inventory

Zheng Sui · Abhijit A. Gosavi · Li Lin

53 citations0/0 files storedEngineering Management Journal

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Supply Chain and Inventory Management Sustainable Supply Chain Management Logistics and Transportation Systems

Abstract

: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.

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References

2018Journal of Business Logistics 1992Production and Operations Analysis 2019Production and Operations Analysis 1999Value of Information in Capacitated Supply Chains 2000Stock Replenishment and Shipment Scheduling for Vendor-Managed Inventory Systems 2003Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning 1981Multi-level production/inventory control systems : theory and practice 2003Simulation-Based Optimization

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