Road networks are critical to a community’s ability to recover from a disaster. The ability to move goods and people efficiently is dramatically affected by disruptions to vulnerable components of the network, especially bridges. Widespread damage to bridges after a natural hazard and limited resources available for repair warrant a need to have an efficient framework to restore the network to the predisaster performance level quickly. Previous studies on postdisaster resilience tend to characterize the recovery based on only one or two performance metrics. This study proposes a decision framework to prioritize bridge repair after a disruptive event using a network performance metric developed using three categories of network performance measures: (1) functional measures defined as the change in total travel distance and total travel time, (2) a topological measure that considers the importance of a bridge to network connectivity modeled with reference to the number of shortest paths passing through each bridge, and (3) a social measure defined with reference to access to healthcare facilities and measured by the change in travel time to an emergency facility. The performance metric is then used to determine an optimal bridge repair sequence that maximizes the network performance during the recovery period. The framework is demonstrated using the road network of Mobile, Alabama, assuming four bridges crossing the Dog River are damaged by a natural hazard. The results of the case study show that the proposed framework is effective in guiding the prioritization of bridge repair after a disaster.

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