Teaching-Learning Based Optimization of Nonlinear Isolation Systems under Far Fault Earthquakes

Seismic isolation systems exposed to far-fault earthquakes can reduce floor accelerations and story drift ratios acceptable levels. However, they exhibit different structural performances in each earthquake due excitation frequency contents. By optimizing the system parameters, their performance may be maintained at best level under earthquakes. In this study, optimization of parameters nonlinear a 5-story benchmark building is performed by Teaching-Learning Based Optimization (TLBO) algorithm minimize peak historical with without exceeding specified base displacement limit. According results analyses, it said that TLBO robust low standard deviations for determining optimum parameters.