Enhancing Supply Chain Resilience in Disruption Caused by Catastrophes Such as Pandemics: An Integrated Grey Analysis-Stochastic Optimization Model - Fady Ahmed; Ibrahim Abdelfadeel Shaban (Decision Making: Applications in Management and Engineering, 2025)
This research presents a comprehensive decision-making model for optimizing global supply chain operations during disruptions caused by catastrophes, e.g., pandemics, making a significant contribution to the supply chain management literature. The model integrates Grey optimal ranking and employs a scenario-based stochastic Mixed-Integer Programming approach to enhance resilience. It addresses the ’ripple effect’ of regional disruptions by modelling simultaneous impacts on supply, demand, and logistics. Computational examples, based on a real-world case during pandemic, validate the model’s effectiveness in minimizing costs and ensuring availability, quality, and emission levels. The study reveals the numerical significance of traditional resilience measures, such as pre-positioning Recovery Materials Inventory and utilizing recovery supplies. Results demonstrate the model’s capacity to mitigate the impacts of multi-regional disruptions. In essence, the research provides a quantifiable and practical contribution, offering insights for resilient supply chain management in the face of pandemic disruptions.