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

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.

Publication Details

Journal
ArXiv.org
Published
2025-05-23
Primary Topic
Facility Location and Emergency Management
Type
article
Field-Weighted Citation Impact
0.00
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article

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

ArXiv.org
Facility Location and Emergency Management
article

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

article en

Abstract

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.

ArXiv.org
Openalex Percentile: Top 42%
Facility Location and Emergency Management
Open Access PDFOpenAlex
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Designing an efficient and equitable humanitarian supply chain dynamically via reinforcement learning · ArXiv.org (2025) | TGRS Research Map | TGRS