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Use of proximal policy optimization for the joint replenishment problem
Vanvuchelen, Nathalie Gijsbrechts, Joren Boute, Robert
Vanvuchelen, Nathalie
Gijsbrechts, Joren
Boute, Robert
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Publication Type
Journal article with impact factor
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Supervisor
Publication Year
2020
Journal
Computers in Industry
Book
Publication Volume
119
Publication Issue
August
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Abstract
Deep reinforcement learning has been coined as a promising research avenue to solve sequential decision making problems, especially if few is known about the optimal policy structure. We apply the proximal policy optimization algorithm to the intractable joint replenishment problem. We demonstrate how the algorithm approaches the optimal policy structure and outperforms two other heuristics. Its deployment in supply chain control towers can orchestrate and facilitate collaborative shipping in the Physical Internet.
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Keywords
Collaborative Shipping, Physical Internet, Joint Replenishment Problem, Machine Learning, Deep Reinforcement Learning, Proximal Policy Optimization