Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 237131, 11 pages
http://dx.doi.org/10.1155/2014/237131
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.

Linked References

  1. D. E. Goldberg, “Genetic algorithms in search, optimization, and machine learning,” Machine Learning, vol. 3, no. 2, pp. 95–99, 1989. View at Google Scholar · View at Zentralblatt MATH
  2. J. R. Koza, Genetic Programming: Vol. 1, on the Programming of Computers by Means of Natural Selection, MIT Press, 1992.
  3. M. Srinivas and L. M. Patnaik, “Adaptive probabilities of crossover and mutation in genetic algorithms,” IEEE Transactions on Systems, Man and Cybernetics, vol. 24, no. 4, pp. 656–667, 1994. View at Publisher · View at Google Scholar · View at Scopus
  4. D. Ortiz-Boyer, C. Hervás-Martínez, and N. García-Pedrajas, “CIXL2: a crossover operator for evolutionary algorithms based on population features,” Journal of Artificial Intelligence Research, vol. 24, pp. 1–48, 2005. View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  5. C. Liu, “A hybrid genetic algorithm to minimize total tardiness for unrelated parallel machine scheduling with precedence constraints,” Mathematical Problems in Engineering, vol. 2013, Article ID 537127, 11 pages, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  6. H. Song, R. Xu, Y. Ma, and G. Li, “Classification of ETM+ remote sensing image based on hybrid algorithm of genetic algorithm and back propagation neural network,” Mathematical Problems in Engineering, vol. 2013, Article ID 719756, 8 pages, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  7. R. Qing-dao-er-ji and Y. Wang, “Inventory based bi-objective flow shop scheduling model and its hybrid genetic algorithm,” Mathematical Problems in Engineering, vol. 2013, Article ID 976065, 7 pages, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  8. D. Tuyttens, H. Fei, M. Mezmaz, and J. Jalwan, “Simulation-based genetic algorithm towards an energy-efficient railway traffic control,” Mathematical Problems in Engineering, vol. 2013, Article ID 805410, 12 pages, 2013. View at Publisher · View at Google Scholar
  9. R. Sali, H. Roohafza, M. Sadeghi, E. Andalib, H. Shavandi, and N. Sarrafzadegan, “Validation of the revised stressful life event questionnaire using a hybrid model of genetic algorithm and artificial neural networks,” Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 601640, 7 pages, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  10. Z. Miao, K. Fu, and F. Yang, “A hybrid genetic algorithm for the multiple crossdocks problem,” Mathematical Problems in Engineering, vol. 2012, Article ID 316908, 18 pages, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  11. T.-H. Yi, H.-N. Li, and M. Gu, “Optimal sensor placement for health monitoring of high-rise structure based on genetic algorithm,” Mathematical Problems in Engineering, vol. 2011, Article ID 395101, 12 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Yen and B. Lee, “Simplex genetic algorithm hybrid,” in Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC '97), pp. 175–180, April 1997. View at Scopus
  13. W. Tang, L. Tong, and Y. Gu, “Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables,” International Journal for Numerical Methods in Engineering, vol. 62, no. 13, pp. 1737–1762, 2005. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  14. S.-F. Hwang and R.-S. He, “A hybrid real-parameter genetic algorithm for function optimization,” Advanced Engineering Informatics, vol. 20, no. 1, pp. 7–21, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. K. E. Mathias, L. D. Whitley, C. Stork, and T. Kusuma, “Staged hybrid genetic search for seismic data imaging,” in Proceedings of the 1st IEEE Conference on Evolutionary Computation, pp. 356–361, June 1994. View at Scopus
  16. H. S. Park, Y. H. Kwon, J. H. Seo, and B.-H. Woo, “Distributed hybrid genetic algorithms for structural optimization on a PC cluster,” Journal of Structural Engineering, vol. 132, no. 12, pp. 1890–1897, 2006. View at Publisher · View at Google Scholar · View at Scopus
  17. S. O. Degertekin, M. P. Saka, and M. S. Hayalioglu, “Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm,” Engineering Structures, vol. 30, no. 1, pp. 197–205, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. C.-M. Chan and K.-M. Wong, “Structural topology and element sizing design optimisation of tall steel frameworks using a hybrid OC-GA method,” Structural and Multidisciplinary Optimization, vol. 35, no. 5, pp. 473–488, 2008. View at Publisher · View at Google Scholar · View at Scopus
  19. G. Li, H. Lu, and X. Liu, “A hybrid genetic algorithm and optimality criteria method for optimum design of RC tall buildings under multi-load cases,” The Structural Design of Tall and Special Buildings, vol. 19, no. 6, pp. 656–678, 2010. View at Google Scholar
  20. J.-T. Tsai, T.-K. Liu, and J.-H. Chou, “Hybrid Taguchi-genetic algorithm for global numerical optimization,” IEEE Transactions on Evolutionary Computation, vol. 8, no. 4, pp. 365–377, 2004. View at Publisher · View at Google Scholar · View at Scopus
  21. H. S. Park and C. L. Park, “Drift control of high-rise buildings with unit load method,” The Structural Design of Tall Buildings, vol. 6, no. 1, pp. 23–35, 1997. View at Google Scholar · View at Scopus
  22. H. S. Park, K. Hong, and J. H. Seo, “Drift design of steel-frame shear-wall systems for tall buildings,” The Structural Design of Tall Buildings, vol. 11, no. 1, pp. 35–49, 2002. View at Publisher · View at Google Scholar · View at Scopus
  23. J. H. Seo, W.-K. Song, Y. H. Kwon, K. Hong, and H. S. Park, “Drift design model for high-rise buildings based on resizing algorithm with a weight control factor,” The Structural Design of Tall and Special Buildings, vol. 17, no. 3, pp. 563–578, 2008. View at Publisher · View at Google Scholar · View at Scopus
  24. AISC-LRFD, Steel Construction Manual, American Institute of Steel Construction, Chicago, Ill, USA, 2011.
  25. S. O. Degertekin, “Optimum design of steel frames using harmony search algorithm,” Structural and Multidisciplinary Optimization, vol. 36, no. 4, pp. 393–401, 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. S. Mazzoni, F. McKenna, M. H. Scott, and G. L. Fenves, OpenSees Command Language Manual, Pacific Earthquake Research Center, University of California at Berkeley, Berkeley, Calif, USA, 2006.
  27. S. Pezeshk, C. V. Camp, and D. Chen, “Design of nonlinear framed structures using genetic optimization,” Journal of Structural Engineering, vol. 126, no. 3, pp. 387–388, 2000. View at Google Scholar · View at Scopus