Steel and Composite Structures

  • 제15권5호
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  • Pages.519-538
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  • 2013
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
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DOI QR Code

An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings

  • Phan, D.T. (Department of Civil Engineering, Universiti Tunku Abdul Rahman) ;
  • Lim, J.B.P. (School of Planning, Architecture and Civil Engineering, Queen's University Belfast) ;
  • Tanyimboh, T.T. (Department of Civil and Environmental Engineering, University of Strathclyde) ;
  • Sha, W. (School of Planning, Architecture and Civil Engineering, Queen's University Belfast)
  • 투고 : 2012.05.28
  • 심사 : 2013.08.05
  • 발행 : 2013.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. Previous GAs in the literature were characterized by poor convergence, including slow progress, that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.

키워드

참고문헌

  1. Autralian/New Zealand $Standard^{TM}$ (2002), AS/NZS1170-0, Structural Design Actions-Part 0: General principles, Sydney, Standards Australia.
  2. Autralian/New Zealand $Standard^{TM}$ (2002), AS/NZS1170-1, Structural Design Actions-Part 1: Permanent, imposed and other actions, Sydney, Standards Australia.
  3. Autralian/New Zealand $Standard^{TM}$ (2002), AS/NZS1170-2, Structural Design Actions-Part 2: Wind actions, Sydney, Standards Australia.
  4. Autralian/New Zealand $Standard^{TM}$ (2005), AS/NZS4600:2005, Cold-formed Steel Structures. Sydney, Standards Australia.
  5. Deb, K. (2000), "An efficient constraint handling method for genetic algorithms", Comput. Method. Appl. Mech., 186(2-4), 311-338. https://doi.org/10.1016/S0045-7825(99)00389-8
  6. Deb, K. (2001), Multi-Objective Optimization Using Evolutionary Algorithms, Chichester: John Wiley and Sons, Inc.
  7. Deb, K. (1997), "Mechanical component design using genetic algorithms", (In: Dasgupta, D. and Michalewicz, Z. eds)., Evolutionary Algorithms in Engineering Applications, New York, Springer, 495-512.
  8. Deb, K. and Agrawal, R.B. (1995), "Simulated binary crossover for continuous space", Complex Systems, 9(2), 115-148.
  9. Deb, K. and Goldberg, D.E. (1989), "An investigation of niche and species formation in genetic function optimization", (In: Schaffer, J.D. ed.), Proceedings of the 3rd International Conference on Genetic Algorithms, San mateo, Morgan Kauffman, 42-50.
  10. Deb, K. and Gulati, S. (2001), "Design of truss-structures for minimum weight using genetic algorithms", Finite Elem. Anal. Des., 37(5), 447-465. https://doi.org/10.1016/S0168-874X(00)00057-3
  11. Goldberg, D.E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Publishing Company, New York, USA.
  12. Goldberg, D.E. and Richardson, J. (1987), "Genetic algorithms with sharing for multimodal function optimization", Proceedings of the 2nd International Conference on Genetic Algorithms, L. Erlbaun Associates, 41-49.
  13. Hasançebi, O., Casbas, S., Dogan, E., Erdal, F. and Saka, M.P. (2010), "Comparison of non-deterministic search technique in the optimum design of the real size steel frame", Comput. Struct., 88(17-18), 1033-1048. https://doi.org/10.1016/j.compstruc.2010.06.006
  14. Hernandez, S., Fontan, A.N., Perezzan, J.C. and Loscos, P. (2005), "Design optimization of steel portal frames", Adv. Eng. Softw., 36(9), 626-633 https://doi.org/10.1016/j.advengsoft.2005.03.006
  15. Issa, H.K. and Mohammad, F.A. (2010), "Effect of mutation schemes on convergence to optimum design of steel frames", J. Constr. Steel Res., 66(7), 954-961. https://doi.org/10.1016/j.jcsr.2010.02.002
  16. Kameshki, E. and Saka, M.P. (2001), "Optimum design of nonlinear steel frames with semi-rigid connections using a genetic algorithm", Comput. Struct., 79(17), 1593-1604. https://doi.org/10.1016/S0045-7949(01)00035-9
  17. Kirk, P. (1986), "Design of a cold-formed section portal frame building system", (In: Yu, W.W. and Senne J.H. eds.), Proceedings of the 8th International Specialty Conference on Cold-formed Steel Structures, University of Missouri-Rolla, St. Louis, Missouri, November, 295-310.
  18. Lim, J.B.P. and Nethercot, D.A. (2004), "Finite element idealization of a cold-formed steel portal frame", J. Struct. Eng. ASCE, 130(1), 78-94. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:1(78)
  19. Miller, B.L. and Shaw, M.J. (1996), "Genetic algorithms with dynamic niche sharing for multimodal function optimization", Proceedings of the IEEE International Conference on Evolutionary Computation, Nagoya, Japan, February, 786-791.
  20. Pezeshk, S., Camp, C. and Chen, D. (2000), "Design of nonlinear framed structures using genetic optimization", J. Struct. Eng. ASCE, 126(3), 382-388. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:3(382)
  21. Phan, D.T., Lim, J.B.P., Sha, W., Siew, C., Tanyimboh, T., Issa, H. and Mohammad, F. (2013), "Design optimization of cold-formed steel portal frames taking into account the effect of topography", Eng. Optimiz., 86, 74-84.
  22. Saka, M.P. (2003), "Optimum design of pitched roof steel frames with haunched rafters by genetic algorithm", Comput. Struct., 81(18-19), 1967-1978. https://doi.org/10.1016/S0045-7949(03)00216-5
  23. Toropov, V.V. and Mahfouz, S.Y. (2001), "Design optimization of structural steelwork using genetic algorithm, FEM and a system of design rules", Eng. Comput., 18(3/4), 437-459. https://doi.org/10.1108/02644400110387118
  24. Yu, E.L. and Sugathan, P.N. (2010), "Ensemble of niching algorithms", Inform. Sci., 180(15), 2815-2833. https://doi.org/10.1016/j.ins.2010.04.008

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