A Fuzzy Prescriptive Analytics Framework for Supply Chain Resilience under Geopolitical Disruptions in the Strait of Hormuz

Geopolitical disruptions have become a source of systemic risk for global supply chains across interconnected transportation, energy, fertilizer, and food systems. Conventional descriptive and predictive analytics are often inadequate under deep uncertainty because geopolitical crises are characterized by ambiguity, limited historical observations, and cascading cross-sector effects. This study proposes an integrated fuzzy prescriptive analytics framework for resilience-oriented supply chain decision-making under geopolitical uncertainty. The framework combines historical evidence, expert elicitation, a Mamdani fuzzy inference system, a weighted aggregation model for food-system stress assessment, and mixed-integer linear programming (MILP). The fuzzy inference system evaluates five disruption drivers—Geopolitical Tension, Maritime Accessibility, Energy Supply Shock, Logistics Delay, and Fertilizer Input Risk—to estimate the Supply Chain Disruption Risk Index (SCDRI) . The Food System Stress Index (FSSI) is then estimated through an expert-informed weighted aggregation of the SCDRI, Energy Supply Shock, and Fertilizer Input Risk. These disruption indicators are translated into deterministic optimization parameters that adjust transportation costs and shortage penalties. The Strait of Hormuz serves as a numerical case study. A MATLAB-based MILP model determines supplier activation, shipment allocation, inventory deployment, emergency procurement, and demand allocation. The results demonstrate that increasing disruption severity raises operating costs and food-system stress while promoting supplier diversification, inventory deployment, transportation reconfiguration, and emergency procurement to maintain supply continuity. The proposed framework provides a transparent, explainable, and reproducible prescriptive analytics methodology that transforms qualitative geopolitical intelligence into quantitative operational decisions, extending supply chain resilience research toward decision support under geopolitical uncertainty.