Optimal Placement of MR Dampers for Structural Control Using Identification Crossover Genetic Algorithm

In order to study the optimal placement of magnetorheological (MR) fluid dampers for structural control, an improved genetic algorithm, i.e. identification crossover genetic algorithm (ICGA), is presented in this paper. The method avoids the constraint violations caused by simple crossover and basic mutation operation. The ICGA produces an identification code. The crossover based on the identification code as well as mutation based on bit-by-bit basis guarantees the fulfillment of constraints. The analytical results by ICGA and general genetic algorithm are compared. It is concluded that the converging speed by ICGA is faster than the converging speed by general genetic algorithm and the control effect by optimal placement is satisfactory.