Steel and Composite Structures

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Topology optimization of nonlinear single layer domes by a new metaheuristic

  • Received : 2014.01.18
  • Accepted : 2014.03.21
  • Published : 2014.06.25
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Abstract

The main aim of this study is to propose an efficient meta-heuristic algorithm for topology optimization of geometrically nonlinear single layer domes by serially integration of computational advantages of firefly algorithm (FA) and particle swarm optimization (PSO). During the optimization process, the optimum number of rings, the optimum height of crown and tubular section of the member groups are determined considering geometric nonlinear behaviour of the domes. In the proposed algorithm, termed as FA-PSO, in the first stage an optimization process is accomplished using FA to explore the design space then, in the second stage, a local search is performed using PSO around the best solution found by FA. The optimum designs obtained by the proposed algorithm are compared with those reported in the literature and it is demonstrated that the FA-PSO converges to better solutions spending less computational cost emphasizing on the efficiency of the proposed algorithm.

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References

  1. American Institute of Steel Construction (AISC) (1991), Manual of Steel Construction-Load Resistance Factor Design, (3rd Edition), AISC, Chicago, IL, USA.
  2. Angeline, P. (1998) "Evolutionary optimization versus particle swarm optimization: Philosophy and performance difference", Proceeding of the 7th International Conference on Evolutionary Programming Conference, San Diego, CA, USA, March.
  3. ANSYS Incorporated (2006), ANSYS Release 10.0.
  4. Bendsoe, M.P. and Sigmund, O. (2003), Topology Optimization: Theory, Methods and Applications, Springer, Berlin, Germany.
  5. Carbas, S. and Saka, M.P. (2012), "Optimum topology design of various geometrically nonlinear latticed domes using improved harmony search method", Struct. Multidis. Optim., 45(3), 377-399. https://doi.org/10.1007/s00158-011-0675-2
  6. Eberhart, R.C. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, IEEE Press, pp. 39-43.
  7. Gandomi, A.H., Yang, X.S. and Alavi, A.H. (2011), "Mixed variable structural optimization using firefly algorithm", Comput. Struct., 89(23-24), 2325-2336. https://doi.org/10.1016/j.compstruc.2011.08.002
  8. Gandomi, A.H., Alavi, A.H. and Talatahari, S. (2013a), Swarm Intelligence and Bio-Inspired Computation: Theory and Applications, Chapter 15: "Structural optimization using krill herd algorithm", Elsevier, (Editors: XS Yang et al.), 335-349.
  9. Gandomi, A.H., Yang, X.S. and Alavi, A.H. (2013b), "Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems", Eng. Comput., 29(1), 17-35. https://doi.org/10.1007/s00366-011-0241-y
  10. Gholizadeh, S. (2013), "Layout optimization of truss structures by hybridizing cellular automata and particle swarm optimization", Comput. Struct., 125, 86-99. https://doi.org/10.1016/j.compstruc.2013.04.024
  11. Gholizadeh, S. and Barati, H. (2011), "Optimum design of structures using an improved firefly algorithm", Int. J. Optim. Civil Eng., 2, 327-340.
  12. Gholizadeh, S. and Barzegar, A. (2013), "Shape optimization of structures for frequency constraints by sequential harmony search algorithm", Eng. Optim., 45(6), 627-646. https://doi.org/10.1080/0305215X.2012.704028
  13. Hassan, R., Cohanim, B., de Weck, O. and Venter, G. (2005), "A comparison of particle swarm optimization and the genetic algorithm", The 1st AIAA Multidisciplinary Design Optimization Specialist Conference, No. AIAA-2005-1897, Austin, TX, USA.
  14. Hu, X., Eberhart, R. and Shi, Y. (2003), "Engineering optimization with particle swarm", IEEE Swarm Intelligence Symposium (SIS 2003), Indianapolis, IN, USA, April, pp. 53-57..
  15. Kaveh, A. and Talatahari, S. (2011), "Geometry and topology optimization of geodesic domes using charged system search", Struct. Multidis. Optim., 43(2), 215-229. https://doi.org/10.1007/s00158-010-0566-y
  16. Makowshi, Z.S. (1984), Analysis, Design and Construction of Braced Domes, Granada Publishing Ltd., London, UK.
  17. MATLAB (2006), The language of technical computing [software], The MathWorks.
  18. Miguel, L.F.F., Lopez, R.H. and Miguel, L.F.F. (2013), "Multimodal size, shape, and topology optimization of truss structures using the Firefly algorithm", Adv. Eng. Softw., 56, 23-37. https://doi.org/10.1016/j.advengsoft.2012.11.006
  19. Rozvany, G.I.N., Bendsoe, M.P. and Kirsch, U. (1995), "Layout optimization of structures", App. Mech. Rev., 48(2), 41-119. https://doi.org/10.1115/1.3005097
  20. Saka, M.P. (2007), "Optimum topological design of geometrically nonlinear single layer latticed domes using coupled genetic algorithm", Comput. Struct., 85(21-22), 1635-1646. https://doi.org/10.1016/j.compstruc.2007.02.023
  21. Salajegheh, E. and Gholizadeh, S. (2012), "Structural seismic optimization using meta-heuristics and neural networks: A review", Comput. Tech. Rev., 5, 109-137. https://doi.org/10.4203/ctr.5.4
  22. Talaslioglu, T. (2012) "Multiobjective size and topolgy optimization of dome structures", Struct. Eng. Mech., Int. J., 43(6), 795-821. https://doi.org/10.12989/sem.2012.43.6.795
  23. Talatahari, S., Gandomi, A.H. and Yun, G.J. (2012), "Optimum design of tower structures by firefly algorithm", Struct. Des. Tall. Spec. Buil., 23(5), 350-361.
  24. Talatahari, S., Kheirollahi, M., Farahmandpour, C. and Gandomi, A.H. (2013), "A multi-stage particle swarm for optimum design of truss structures", Neural. Comput. Appl., 23(5), 1297-1309. https://doi.org/10.1007/s00521-012-1072-5
  25. Vanderplaats, G.N. (1984), Numerical Optimization Techniques for Engineering Design: With Application, (2nd Ed.), McGraw-Hill, NewYork, NY, USA.
  26. Yang, X.S. (2009), "Firefly algorithms for multimodal optimization", Stochastic Algorithms: Foundations and Applications (Eds O. Watanabe and T. Zeugmann), SAGA 2009, Lecture Notes in Computer Science, 5792, Springer-Verlag, Berlin, pp. 169-178.
  27. Yang, X.S. (2010), "Firefly algorithm, Levy flights and global optimization", Research and Development in Intelligent Systems XXVI, (Eds M. Bramer, R. Ellis, M. Petridis), Springer London, UK, pp. 9-18.

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