Resilience-based seismic design optimization of highway RC bridges by response surface method and improved non-dominated sorting genetic algorithm

In this study, a resilience-based multi-objective optimal seismic design method is proposed to maximize the seismic performance and minimize the material cost of highway reinforced concrete (RC) bridges. The size of the elastomeric bearings and cross-sectional arrangement of the RC pier are selected as the design parameters. To improve the accuracy and efficiency, the nonlinear time history analysis based on cloud analysis approach and response surface method are applied to obtain the seismic resilience during the seismic optimization process. The optimization problem is solved through an improved non-dominated sorting genetic algorithm (NSGA-II). Following, the proposed method is applied to a highway RC bridge, and the optimal design schemes are determined from the Pareto optimal solutions. The numerical results show that the resilience response surface model can be used to predict the seismic resilience of bridges. Moreover, the proposed method can minimize the material cost and maximize the seismic resilience by adjusting the damage grades of various bridge components.