Multi-objective optimal design of sliding base isolation using genetic algorithm

In this paper, a multi-objective optimization for the optimal design of sliding isolation systems for suppression of seismic responses of building structures is presented. Due to the presence of several parameters affecting the performance of sliding base isolation systems, applying a rigorous multi-objective optimization technique is inevitable. Hence, in this study, the genetic algorithm is used to find optimal values of isolator parameters, including coefficient of friction, mass of base raft and the damping ratio of the restoring force device. The restoring device, which is composed of a linear spring and a linear viscous damper, is attached to the base raft in order to minimize the during-event and after-event sliding displacement of the base raft. The simultaneous minimization of the building’s top story displacement and its acceleration, and also the base raft’s displacement, are considered as the objective functions. In order to satisfy the objective functions, a fast and elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to find a set of Pareto-optimal solutions. The isolated building is modeled as a shear-type structure having one lateral degree of freedom at each story level. A ten-story building is used for the numerical study and an ensemble of seven earthquake records is considered for the analysis. The results indicate that by applying the final design parameters obtained from the optimal values found by the NSGA-II approach corresponding to each individual record, the sliding isolator system effectively suppresses the structural seismic responses. Also, it is found that the restoring device with an optimal viscous damper might slightly reduce the performance of the isolation system, but is strongly effective in controlling the maximum base raft displacement and the residual base raft displacement.