Optimization Of Concrete Filled Steel Tubular Frame Based On Genetic Algorithms

Concrete Filled Steel Tubular(CFST) frame system has been applied in high-rise buildings increasingly in recent years because of its high load-carrying capacity, good plastic and toughness, prominent economic benefits and concise steps of construction etc. CFST frame is not only a major structure form of the buildings, which have been built in our country, but also has a good developing prospect in the future. Optimization researches on CFST frame are still scarce. In order to guarantee the security of this kind of building, and improve the investment benefit of the building, it is necessary to find the rational and scientific design, optimization method. In this paper, the more accurate force had been calculated by writing the Fortran program of finite element to compute CFST frames with composite bending modulus and composite compressive modulus. The improved genetic algorithm based on real number encoding was introduced for the first time. The selection, crossover and mutation algorithm of genetic algorithms and other parameters coded were designed. Direct comparison-proportional method was applied to handle restriction optimization problems. The structure optimization programs were written for CFST column and steel beam in Matlab, and applied to the example. Compared with original datum, the result is shown that this method can be used conveniently. It is easy to receive the optimal answer with the genetic algorithms, which can solve the scope of problem largely, and require less initial conditions. The research is an application of new intelligent optimization theory to the CFST frame. It is not only significative for the improvement of design theory and decreasing investment but also helpful in designing other structure forms rationally.