Dynamic emergency inspection routing and restoration scheduling to enhance the post-earthquake resilience of a highway–bridge network

• Updating inspection and restoration plans in real time improves network resilience. • Inaccurate estimation of network damages leads to low levels of network resilience. • Different levels of dynamism affect the performance of the dynamic model. • Hybrid genetic algorithm effectively solves dynamic routing and scheduling problems. In the immediate aftermath of earthquakes, effective scheduling of emergency restoration for transportation networks depends fundamentally on information about damage to those networks, which for the most part can only be acquired via a lengthy process of inspection. This paper proceeds from the insight that, rather than waiting to commence restoration activities until after all inspection activities are completed, damage information revealed gradually via inspection efforts could be incorporated into parallel scheduling of inspection routes and restoration schedules, allowing inspection and restoration to occur simultaneously, thus more efficiently boosting transportation networks’ resilience. To achieve this, however, it will be necessary to understand the real-time interaction between inspection and restoration, as well as such interaction's impacts on the inspection-routing and restoration-scheduling process. Assuming that multiple inspection and restoration crews operate simultaneously and that their optimal routes and schedules are updated dynamically whenever additional inspection information is obtained, this study proposes an integer program for modeling inspection-routing and restoration-scheduling problems and determining the optimal inspection routes and restoration schedules for damaged highway–bridge networks, with the specific aim of maximizing a resilience measure, network travel time. The results of a case study using the proposed method and data from the 2008 Wenchuan Earthquake in China show that, as compared to a traditional inspection-restoration model, simultaneously performing and dynamically scheduling inspection and restoration can significantly boost networks’ resilience.