Robust multi-objective optimization design of TMD control device to reduce tall building responses against earthquake excitations using genetic algorithms

Tuned Mass Dampers (TMDs) are a well-accepted control device widely used by the civil engineering community. The main purpose of this study is the robust multi-objective optimization design of this device using Genetic Algorithms (GAs) to control the structural vibrations against earthquakes. To enhance the performance of the TMD system, its parameters, including mass, stiffness, and damping ratio, have been optimally designed using multi-objective genetic algorithms. For doing this, three non-commensurable objective functions, namely: maximum displacement, maximum velocity, and maximum acceleration of each floor, are considered, which are to be minimized simultaneously. For this purpose, a fast and elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. Moreover, in order to take into account the uncertainties existing in the system, a robust design optimization procedure is performed using the Hammersley sequence sampling approach. In this study, the example building is modeled as a 3-D frame, and its responses are evaluated using coupled multi-mode analysis. From the numerical results of the study, it is found that the robust TMD system is capable of providing a reduction of about 28% on maximum displacement of the building.