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Mathematical Problems in Engineering
Volume 2014, Article ID 237131, 11 pages
Research Article

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

1Department of Architectural Engineering, Yonsei University, Seoul 120-749, Republic of Korea
2Center for Structural Health Care Technology in Building, Yonsei University, Seoul 120-749, Republic of Korea
3Design Department, TSEC Group, Seoul 133-120, Republic of Korea
4Department of Architecture, Catholic University of Daegu, Gyeongsan-si 712-702, Republic of Korea

Received 17 October 2013; Accepted 8 April 2014; Published 6 May 2014

Academic Editor: Stefano Lenci

Copyright © 2014 Hyo Seon Park et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for 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 algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.