Supply chain risks imposed by natural disasters can be reduced by discovering an optimal combination of governmental and manufacturing strategies. These strategies should promote the adaptation, resilience, and resistance of enterprises to rare but damaging events, contributing to a decrease in risk and vulnerability. This. research focuses on modeling, measuring, and managing natural disaster risks and their impact on circular supply chains. Specifically, the research aims to address the following questions:
1) How can optimal decisions of an enterprise influence the event’s magnitude, impact, and frequency (e.g., construction of dikes against flood events)?
2) How to avoid the circulation of risks in a circular supply chain in case of major disruptions?
Addressing both questions would be of great value for global supply chain sustainability practices including the benefit of the implementation of a circular economy in agriculture, helping to prevent collapses in the production and supply of food in case of natural disasters or other major events.
By developing novel tools for optimization under uncertainty, the research aims to explicitly account for the interdependence of natural disasters in time (e.g., cascading effects in a multi-period perspective), space (e.g., multi-region perspective) and type (i.e., multi-hazard perspective) to reduce supply chain vulnerability in case of major disruptions:
The expected output of this research includes enterprise loss and capital distributions, as well as a methodological framework to introduce decision-dependent uncertainties into multi-stage optimization problems and the framework for modeling circular risks in circular supply chains.