MARLIM: Multi-Agent Reinforcement Learning for Inventory Management

• URL: http://arxiv.org/abs/2308.01649v1
• Date: Thu, 3 Aug 2023 09:31:45 GMT
• Title: MARLIM: Multi-Agent Reinforcement Learning for Inventory Management
• Authors: R\'emi Leluc, Elie Kadoche, Antoine Bertoncello, S\'ebastien Gourv\'enec
• Abstract summary: This paper presents a novel reinforcement learning framework called MARLIM to address the inventory management problem. Within this context, controllers are developed through single or multiple agents in a cooperative setting. Numerical experiments on real data demonstrate the benefits of reinforcement learning methods over traditional baselines.
• Score: 1.1470070927586016
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Maintaining a balance between the supply and demand of products by optimizing replenishment decisions is one of the most important challenges in the supply chain industry. This paper presents a novel reinforcement learning framework called MARLIM, to address the inventory management problem for a single-echelon multi-products supply chain with stochastic demands and lead-times. Within this context, controllers are developed through single or multiple agents in a cooperative setting. Numerical experiments on real data demonstrate the benefits of reinforcement learning methods over traditional baselines.

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