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Designing an efficient and equitable humanitarian supply chain dynamically via reinforcement learning

arXiv 2505.17439 ↗First posted 23 May 2025cs.LG cs.AIcited by 0

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Abstract (arXiv)

This study designs an efficient and equitable humanitarian supply chain dynamically by using reinforcement learning, PPO, and compared with heuristic algorithms. This study demonstrates the model of PPO always treats average satisfaction rate as the priority.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). First posted on arXiv 23 May 2025.

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