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.

翻译：通过在供需之间维持平衡来优化补货决策是供应链行业最重要的挑战之一。本文提出了一种名为MARLIM的新型强化学习框架，用于解决具有随机需求与交付周期的单层级多产品供应链库存管理问题。在此背景下，控制器通过单智能体或多智能体协作方式构建。基于真实数据的数值实验表明，强化学习方法相较于传统基线具有显著优势。