Resilient Supply Chain Networks in the Age of Geopolitical Disruption: A Network Optimization Approach Using Digital Twins and Scenario-Based Simulation - Opeyemi Morenike Filani; John Oluwaseun Olajide; Grace Omotunde Osho (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024)
Geopolitical disruptions—including trade wars, regional conflicts, economic sanctions, and shifting diplomatic alliances—have increasingly exposed the vulnerabilities of global supply chain networks. These disruptions often result in supply shortages, escalating costs, and logistical bottlenecks, highlighting the urgent need for more resilient and adaptive supply chain strategies. This explores a novel network optimization framework that integrates digital twin technology with scenario-based simulation to enhance supply chain resilience in the face of geopolitical uncertainties. Digital twins—virtual replicas of physical supply chain systems—enable real-time monitoring, predictive analytics, and dynamic scenario testing by integrating data from sensors, enterprise resource planning (ERP) systems, and external geopolitical risk indicators. Scenario-based simulation complements this by modeling hypothetical disruption events, including sudden trade barriers, supplier bankruptcies, and transportation shutdowns. Together, these tools enable decision-makers to assess the impact of diverse geopolitical shocks and to evaluate mitigation strategies in advance. This also applies advanced network optimization methods such as mixed-integer programming, stochastic optimization, and robust optimization to identify optimal supply chain configurations under various risk scenarios. These models enable organizations to dynamically reconfigure supply chain structures, rebalance inventories, and adjust sourcing strategies to minimize costs while maintaining service continuity. Through case studies across sectors including automotive, pharmaceuticals, and electronics, this research demonstrates that the combined use of digital twins, scenario simulations, and network optimization can significantly improve supply chain agility, visibility, and robustness. The findings emphasize that technological integration, proactive risk management, and collaborative strategies are essential for building future-ready supply chain networks capable of withstanding geopolitical disruptions. Ultimately, this calls for greater adoption of digital twin-enabled optimization frameworks and highlights the need for continued research into AI-augmented, adaptive supply chain models that address complex, fast-evolving global risks.