OPTIMAL PLACEMENT OF MRFD USING IMPROVED GENETIC ALGORITHMS

In order to study optimal placement of magnetorheological fluid damper (MRFD) in semi-actively controlled structures, an improved genetic algorithm is presented in this paper. To avoid the constraint violations caused by crossover and basic mutation operation of the general genetic algorithms, a new genetic operation approach, i.e. improved genetic algorithm, is applied. The improved genetic algorithm produces an identification code for crossing and two-gene place to mutate. Thus, the improved crossover and mutation operation guarantee the fulfillment of constraints. The analytical results of the improved genetic algorithm and the general genetic algorithm are compared. It is concluded that the converging speed of the improved genetic algorithm is faster than that of general genetic algorithm and the control effect by optimal placement is satisfactory.