Decision-Making Frameworks Enhancing Interdependent Infrastructures Resilience
Modern societies depend on interconnected infrastructure systems—such as power, transportation, water, and communication networks—whose failures can cascade across sectors, amplifying the impact of large-scale disruptions. Events like the 2003 Northeast blackout and Hurricane Irma in 2017 have revealed the vulnerability of these systems and underscored the need for rapid, reliable decision-making tools to guide restoration and enhance resilience. This research develops optimization-based decision-making frameworks to support the prioritization and allocation of limited resources and repair crews across interdependent networks following major disruptions. The methodology integrates network optimization models, resilience analytics, and data-driven simulation to identify optimal restoration sequences and interdependency-aware recovery strategies. From a managerial and societal perspective, these frameworks enable infrastructure administrators to make faster, more informed restoration decisions, thereby reducing downtime, minimizing cascading failures, and mitigating the impacts on vulnerable communities. Ultimately, this work advances national security, public safety, and health resilience by providing a scalable and analytical foundation for restoring critical infrastructure systems under uncertainty.
Project Title: Integrative Decision-Making Framework to Enhance the Resiliency of Interdependent Critical Infrastructures.
Funding Agency: NSF CRISP.
Utility Partners: Department of Transportation and Stormwater Services, Public Works and Utility Services (City of Tampa).
Role: Graduate Research Assistant