Resource-based seismic resilience optimization of the blocked urban road network in emergency response phase considering uncertainties

Abstract

For disaster management organizations, determining the required resources for pre-positioning and optimal resources allocation schedules are important problems in the preparation planning stage for emergency restoring blocked urban road networks. This study bridges the gap between seismic simulation of network obstruction due to roadside collapsed buildings, resource allocation scheduling, and Bruneau's proposed resilience index to assessment the required resources and optimal restoration planning. There are uncertainties in different parts of network restoration planning such as uncertainty in earthquake magnitude, fault rupture location, seismic intensity, building collapse, debris width, debris volume, and restoration time. Uncertainty in a part affects the realization of the next dependent part, therefore integrated framework is needed for realistic restoration planning that has not been addressed in the literature. In this paper, uncertainties are modeled based on probabilistic models to estimate the expected value of path restoration time. Topology-Demand base network functionality index is proposed to evaluate network performance after the earthquake. To optimize resilience, an algorithm based on Simulated Annealing is designed which determines the maximum required resources and optimal task sequences. The proposed framework is showcased by a road network in Tehran metropolis. Equivalent functionality curves are introduced to compare the effects of resource number on network emergency resilience. The optimization results indicate the six resources restore the network within two defined target times. Also, the results reveal that the effect of resource number on reducing the completion time decreases with increasing resources.