2953. Optimizing the Middle Corridor: A Multi-Agent AI Approach
Invited abstract in session Sustainable and Generative AI in SCM for Emerging Economies , stream OR for Development.
Authors (first author is the speaker)
| 1. | Bruno Kamdem
|
| Department of Business Management, SUNY Farmingdale State College, School of Business | |
| 2. | Nahid Jafari
|
| Business Management, SUNY Farmingdale State College, School of Business |
Abstract
Geopolitical volatility and the closure of the Strait of Hormuz have forced a critical shift toward the Middle Corridor or Trans-Caspian International Transport Route (TITR). This paper addresses the resulting coordination crisis between sovereign governments and private carriers using a Multi-Agent Deep Deterministic Policy Gradient (MADDPG) framework. We implement a Centralized Training, Decentralized Execution (CTDE) architecture to solve a high-dimensional stochastic differential game.
Keywords
- Machine Learning
- Supply Chain Management
- Control Theory
Status: accepted
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