Simultaneous Multi-objective Optimization of Semi-active Intermediate Isolation System and Building Structure

Recently, to reduce seismic responses, dozens of high-rise buildings in Japan and Korea have adopted the intermediate isolation system (IIS). These applications have shown successful response reduction performance for tall buildings. The important dynamic responses of building structures with the IIS are the peak intermediate isolator drift (IID), and the peak inter-story drift (ISD). The semi-active intermediate isolation system (SAIIS) was developed to more effectively reduce these seismic responses. In previous study, the authors showed that the SAIIS using magnetorheological dampers successfully reduced both the IID and the ISD. However, the optimal design of the SAIIS only was conducted, without considering the building structure. If both the SAIIS and the building structure properties are considered in the optimal design procedure, more effective optimal design for both the SAIIS and the building structure can be achieved. In this research, a simultaneous multi-objective optimization (MOO) method of the SAIIS and the building structure is proposed to achieve this. Genetic algorithm was selected for simultaneous MOO of the SAIIS and the building structure. The fuzzy inference controller was selected as a control algorithm. The authors show that in comparison to the sequential optimization procedure that practical applications generally use, the simultaneous MOO method can provide much better control capacity and structural design process.