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 systemsfor suppression of seismic responses of building structures is presented. due to the presence of severalparameters 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 findoptimal values of isolator parameters, including coefficient of friction, mass of base raft and the dampingratio of the restoring force device. the restoring device, which is composed of a linear spring and a linearviscous damper, is attached to the base raft in order to minimize the during-event and after-event slidingdisplacement of the base raft. the simultaneous minimization of the building's top story displacement andits acceleration, and also the base raft's displacement, are considered as the objective functions. in orderto satisfy the objective functions, a fast and elitist non-dominated sorting genetic algorithm (nsga-ii) isused to find a set of pareto-optimal solutions. the isolated building is modeled as a shear-type structurehaving one lateral degree of freedom at each story level. a ten-story building is used for the numericalstudy and an ensemble of seven earthquake records is considered for the analysis. the results indicate thatby applying the final design parameters obtained from the optimal values found by the nsga-ii approachcorresponding to each individual record, the sliding isolator system effectively suppresses the structuralseismic responses. also, it is found that the restoring device with an optimal viscous damper might slightlyreduce the performance of the isolation system, but is strongly effective in controlling the maximum baseraft displacement and the residual base raft displacement.