Optimal Bridge Restoration Sequence for Resilient Transportation Networks

Transportation networks are necessary infrastructure elements to provide aid to impacted areas after the occurrence of an extreme event. Without functional roads, recovering other damaged facilities and lifelines would be slow and difficult. Therefore, restoring the damages of transportation networks, specifically bridges as their most vulnerable elements, is among the first priorities of disaster management officials. This paper presents a new methodology for scheduling the restoration of damaged bridges. The problem is formulated as a multi-objective combinatorial optimization solved by Genetic Algorithms, which minimizes the time to connect the selected critical locations and maximizes the resilience of the transportation network. The main purpose of developing the algorithm was to provide a restoration plan which is practical to be used by decision makers at the time of an event, yet based on solid computations rather than mere engineering judgment. The algorithm is examined with a numerical example. The presented algorithm can be considered as the enhancement of previous work performed at Lehigh University. The results show that the new optimization setup improved the solution quality and efficiency compared to the previous techniques.