Distributional reinforcement learning for inventory management in multi-echelon supply chains

Distributional reinforcement learning for inventory management in multi-echelon supply chains

Reinforcement Learning (RL) is an effective method to solve stochastic sequential decision-making problems. This is a problem description common to supply chain operations, however, most RL algorithms are tailored for game-based benchmarks. Here, we propose a deep RL method tailored for supply chain...

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Bibliographic Details
Main Authors: Guoquan Wu, Miguel Ángel de Carvalho Servia, Max Mowbray
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Digital Chemical Engineering
Subjects:
Distributional reinforcement learning
Optimal control
Inventory management
Multi-echelon supply chains
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2772508122000643

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http://www.sciencedirect.com/science/article/pii/S2772508122000643

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