ABSTRACT
Many critical infrastructure networks that dot the global landscape often rely on each other in different ways for each to be functional. Government planning documents around the world recognize the interdependence of these infrastructure networks. But naturally infrastructure networks do not exist for their own operation but because society relies upon them for convenience, productivity, and health, among others. Recent large-scale disruptions to critical infrastructure, primarily due to natural disasters whose frequency appears to be increasing, have left communities devastated for extended periods. As such, planning for the resilience of critical cyber-physical-social networks should emphasize the social aspects of disruptions. In this work, we study the problem of the restoration of interdependent infrastructure networks after the occurrence of a disruptive event with a focus on the vulnerability of the society that interacts with the networks. We integrate (i) a resilience-driven multi-objective mixed-integer programming formulation that schedules the restoration of disrupted demand nodes in each network with (ii) a geographically distributed index of social vulnerability that measures the impact to the community surrounding the disrupted demand nodes. This model integration is illustrated with an example of community resilience in Shelby County, Tennessee.
