Managing Geological Uncertainty in Critical Mineral Supply Chains: A POMDP Approach with Application to U.S. Lithium Resources
It addresses the problem of strategic decision-making for policymakers in critical mineral supply chains, offering a systematic approach to manage geological uncertainty, though it is an incremental application of an existing method to a new domain.
The paper tackles the challenge of geological uncertainty in critical mineral supply chains by applying Partially Observable Markov Decision Processes (POMDPs) to optimize sourcing decisions, demonstrating through a U.S. lithium case study that POMDP-based policies achieve superior outcomes compared to traditional approaches, especially with imperfect initial reserve estimates.
The world is entering an unprecedented period of critical mineral demand, driven by the global transition to renewable energy technologies and electric vehicles. This transition presents unique challenges in mineral resource development, particularly due to geological uncertainty-a key characteristic that traditional supply chain optimization approaches do not adequately address. To tackle this challenge, we propose a novel application of Partially Observable Markov Decision Processes (POMDPs) that optimizes critical mineral sourcing decisions while explicitly accounting for the dynamic nature of geological uncertainty. Through a case study of the U.S. lithium supply chain, we demonstrate that POMDP-based policies achieve superior outcomes compared to traditional approaches, especially when initial reserve estimates are imperfect. Our framework provides quantitative insights for balancing domestic resource development with international supply diversification, offering policymakers a systematic approach to strategic decision-making in critical mineral supply chains.