Deep reinforcement learning for inventory control: A roadmap
Apr 16, 2022 · Deep reinforcement learning (DRL) has shown great potential for sequential decision-making, including early developments in inventory control. Yet, th…
Keywords: Inventory Policy, Multi-Echelon, Reinforcement Learning, Supply Chain Management, Q-Learning Article history: Received 30 July 2021, first decision: 18 August 2021, accepted 24 …
Reinforcement Learning presents a paradigm shift in supply chain management by offering adaptive, autonomous, and data-driven decision-making capabilities. Its application in …
Deep Reinforcement Learning for Inventory Control: a Roadmap
We study a joint pricing and inventory control problem for perishables with positive lead time in a finite horizon periodic-review system. Unlike most studies considering a continuous density …
Reinforcement Learning (RL) presents a transformative approach to inventory management by offering adaptive, data- driven strategies capable of navigating uncertainty and dynamic …
Reinforcement Learning for Inventory Management
Jul 23, 2025 · Effective inventory management helps businesses minimize costs related to holding inventory, reduce waste, avoid stockouts and optimize supply chain efficiency.
Deep reinforcement learning (DRL) is a subset of machine learning that com-bines reinforcement learning with deep neural networks, enabling it to make sequential decisions and optimize …
1. Introduction Supply chain inventory management (SCIM) is a complex sequential decision-making problem consisting of deter-mining the optimal quantity of products to produce at the …
Inventory Control and Supply Chain Optimization with Reinforcement Learning
Feb 7, 2021 · Reinforcement Learning (RL) is a sub-discipline of machine learning that optimizes repeated, sequential decisions for a global business-centric goal. RL is often seen in …
Reinforcement Learning for Dynamic Inventory Management
May 2, 2025 · 📦 Reinforcement Learning for Dynamic Inventory Management Optimize inventory decisions using Reinforcement Learning (RL) to reduce holding costs, avoid stockouts, and …
Jul 5, 2021 · However, RL takes longer time to arrive at solutions, necessitating future research on identifying and improving trade-o s between the use of AI and mathematical models are …
Reinforcement Learning Approach for Efficient Inventory Policy …
Abstract Read online Background: Inventory policy highly influences Supply Chain Management (SCM) process. Evidence suggests that almost half of SCM costs are set off by stock-related …