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

This work addresses humanitarian logistics for disaster response, but appears incremental as it applies existing methods like PPO to this domain.

The study tackled the problem of designing a humanitarian supply chain by using reinforcement learning (PPO) to dynamically optimize efficiency and equity, demonstrating that the model prioritizes average satisfaction rate.