Optimization Research For Steel-concrete Composite Members Based On Accelerating Genetic Algorithm

With the development of economy and society and the increase of human demand, high-rise buildings are used more widely. Steel-concrete composite structure, which owns excellent characters of steel and concrete, is widely used in high-rise building as a new form of structure. In recent years, because the usage amount of steel-concrete composite member is increasing, the materials used for composite beam and column used hold a large proportion in high-rise building. To reduce the material consumption and the project cost, it is crucial to optimize the combination structures in a reasonable manner. The optimization for steel-concrete composite structure was studied by combining accelerating genetic algorithm and mechanical knowledge in this study, which can not only satisfy the conditions of bearing capacity, but also meet the requirements of material cost.This study constructed the optimization models, where the research objects were the column of concrete filled square steel tubular and steel-concrete composite beam respectively, and the objective functions were component cost minimum, the optimization variables were parameters which control the cross section, and the constraint conditions were building constraints based on the steel-concrete composite structure design norms. Then the calculation method of structure optimization, which combined accelerating genetic algorithm with mechanical analysis, was proposed, finally examples solved by using structure optimization program were showed. The cost of concrete filled square steel tubular after optimization could be 23.4% less than the original design, and that of steel-concrete composite beam could be 38.3% less than the original one. The speed of optimizing through accelerating genetic algorithm was also improved by 28% and 25.8% respectively than standard genetic algorithm.The results showed that the consumption of material was reduced apparently by accelerating genetic algorithm compared with the original design. Compared with the results obtained through standard genetic algorithm, the speed and precision were all improved. It is feasible to solve problems of steel-concrete composite optimization by accelerating genetic algorithm, which has high economic efficiency and application value, the research provides important reference for the structure optimization design.