Two major extreme-weather events occurred in New York State between 2011 and 2012. Each with the odds of a 100-year occurrence suggesting that such extreme events are the region's new normal. City and state policy-makers, in response, are studying how to develop a network of robust, resilient critical infrastructure facilities. These studies, however, typically fail to address interdependencies among critical infrastructures and lack a quantitative tool to investigate the maximum resilience possessed by a given infrastructure facility in the face of climate-change-induced hazards. We propose a multi-stage stochastic mathematical program to maximize network resilience given: i) random arrival of extreme events; ii) the network's inherent capacity to withstand and cope with the aftermath of exogenous shocks; iii) pre-, during-, and post-event strategies available to enhance system operability; and iv) budgeting and technological restrictions facing policy-makers. Our approach allows both qualitative and quantitative paradigms to interact. Our model thus clarifies how to allocate resources proactively and how the network's absorptive, adaptive, and restorative capacities can be coordinated to enhance overall system resilience. Our findings suggest that an integrated planning approach combined with smart allocation of resources across a network's main elements creates a greater degree of resilience while utilizing less costly resilience-enhancing strategies.
Beheshtian, A; Donaghy, KP; Geddes, RR; Rouhani, OM
Planning resilient motor-fuel supply chain
International Journal Of Disaster Risk Reduction