Immune Genetic Algorithm for Optimizing Reinforced-Concrete Frame- Shear Wall Structure

Abstract

An immune genetic algorithm (IGA) is proposed to optimize the reinforced concrete (RC) frame-shear wall structures. Compared with the simple genetic algorithm (SGA), this algorithm has adaptive search capabilities for the future knowledge being used in the process of population evolution. Since the concrete grade of floors and the layout of walls are translated to binary codes, the implementation of this algorithm is not affected by the complexity of the structures. With I-typed vaccine, the continuous vertical stiffness of structure is ensured; With II-typed vaccine, the structures conforms to all the specifications which including floor shift angle, floor displacement ratio and period ratio. At the element level, the optimizing results satisfy all the specifications required by the current Chinese Codes. In this way, a computer program is created to get optimum design schemes.