Bridge Maintenance Scheduling in Consideration of Resilience Against Natural Disasters - Ishibashi, Ken; Furuta, Hitoshi; Nakatsu, Koichiro (Frontiers in Built Environment, 2020)
This study aims to develop a bridge maintenance plan in consideration of the resilience of a road network against natural disasters. Toward this end, the reliability of a road network is calculated using the failure probability of bridges as an evaluation index. Bridges are social infrastructure that are essential for maintaining daily life; however, their repair and reinforcement can cause the partial disruption of road networks. Nonetheless, insufficient bridge maintenance can cause serious harm to people in an emergency, such as after an earthquake. Therefore, studies have aimed to develop long-term plans to minimize the life-cycle cost (LCC) of bridges. Other studies have measured the probability of bridge failure and developed countermeasures against natural disasters to improve the reliability and resilience of bridges. Unfortunately, studies have focused on these aspects independently of one another, even though an effective bridge maintenance plan requires them to be considered together. A plan that both minimizes LCCs and improves resilience is expected to be useful for sustainable bridge management. We search for candidates for optimal plans for long-term bridge maintenance by using a genetic algorithm (GA). The proposed method has three objectives: (1) minimization of bridge repair and reinforcement costs, (2) minimization of disruption to social activities (i.e., user cost) due to bridge maintenance, and (3) maximization of resilience against natural disasters. First, the GA is used to search for a plan with minimized maintenance cost and a flexible work period by considering uncertainties related to bridges. The remaining indices are optimized based on the flexible period. The resilience of bridges is measured through Monte Carlo simulations by using the failure probability based on the bridge state at a certain point. Numerical experiments are conducted to demonstrate the usefulness of this method for establishing a sustainable bridge maintenance plan.