Resizing Technique-Based Hybrid Genetic Algorithm for Optimal Drift Design of Multistory Steel Frame Buildings

Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizingtechnique-based hybrid genetic algorithmfor the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithmis combined with a resizingtechnique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizingtechnique-based hybrid genetic algorithmproposed in this paper is applied to the minimum weightdesign of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithmare compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithmshows clear improvements in convergence properties.