Journal
COMPUTERS IN INDUSTRY
Volume 119, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.compind.2020.103239
Keywords
Collaborative Shipping; Physical Internet; Joint Replenishment Problem; Machine Learning; Deep Reinforcement Learning; Proximal Policy Optimization
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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. (C) 2020 Elsevier B.V. All rights reserved.
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