Advances in Computational Design

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An enhanced simulated annealing algorithm for topology optimization of steel double-layer grid structures

  • Mostafa Mashayekhi (Department of Civil Engineering, Vali-e-Asr University of Rafsanjan) ;
  • Hamzeh Ghasemi (Department of Civil Engineering, Vali-e-Asr University of Rafsanjan)
  • Received : 2024.01.08
  • Accepted : 2024.05.16
  • Published : 2024.04.25
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Abstract

Stochastic optimization methods have been extensively studied for structural optimization in recent decades. In this study, a novel algorithm named the CA-SA method, is proposed for topology optimization of steel double-layer grid structures. The CA-SA method is a hybridized algorithm combining the Simulated Annealing (SA) algorithm and the Cellular Automata (CA) method. In the CA-SA method, during the initial iterations of the SA algorithm, some of the preliminary designs obtained by SA are placed in the cells of the CA. In each successive iteration, a cell is randomly chosen from the CA. Then, the "local leader" (LL) is determined by selecting the best design from the chosen cell and its neighboring ones. This LL then serves as the leader for modifying the SA algorithm. To evaluate the performance of the proposed CA-SA algorithm, two square-on-square steel double-layer grid structures are considered, with discrete cross-sectional areas. These numerical examples demonstrate the superiority of the CA-SA method over SA, and other meta-heuristic algorithms reported in the literature in the topology optimization of large-scale skeletal structures.

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References

  1. Amiri, H., Radfar, N., Arab Solghar, A. and Mashayekhi, M. (2023), "Two improved teaching-learning-based optimization algorithms for the solution of inverse boundary design problems", Soft Comput., https://doi.org/10.1007/s00500-023-08415-2. 
  2. Azad, S.K., Hasancebi, O. and Kazemzadeh Azad, S. (2013), "Upper bound strategy for metaheuristic based design optimization of steel frames", Adv. Eng. Softw., 57, 19-32. https://doi.org/10.1016/j.advengsoft.2012.11.016 
  3. Babaei, M., Atasoy, A., Hajirasouliha, I. and Mollaei, S. (2022), "Numerical solution of beam equation using neural networks and evolutionary optimization tools", Adv. Comput. Des., 7(1), 19-35. https://doi.org/10.12989/acd.2022.7.1.001. 
  4. Bouzouiki, M.E., Sedaghati, R. and Stiharu, I. (2021), "A non-uniform cellular automata framework for topology and sizing optimization of truss structures subjected to stress and displacement constraints", Comput. Struct., 242, 106394. https://doi.org/10.1016/j.compstruc.2020.106394. 
  5. Canyurt, O.E. and Hajela, P. (2005), "A cellular framework for structural analysis and optimization", Comput. Methods Appl. Mech. Eng., 194, 3516-3534. https://doi.org/10.1016/j.cma.2005.01.014 
  6. Cerny, V. (1985), "Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm", J. Opt. Theory. Appl., 45, 41-51. https://doi.org/10.1007/BF00940812 
  7. Cho, A. and Kang, T.H.K. (2021), "Computer-based design optimization of post-tensioned anchor for single-strand", Adv. Comput. Des., 6(4), 19-35. https://doi.org/10.12989/acd.2021.6.4.339. 
  8. Cui, Y., Geng, Z., Zhu, Q. and Han, Y. (2017), "Review: Multi-objective optimization methods and application in energy saving", Energy, 125, 681-704. https://doi.org/10.1016/j.energy.2017.02.174 
  9. Dehghani, M., Mashayekhi, M. and Salajegheh, E. (2016), "Topology optimization of double- and triple-layer grids using a hybrid methodology", Eng. Optim., 48, 1333-1349. https://doi.org/10.1080/0305215X.2015.1105968 
  10. Dehghani, M., Mashayekhi, M. and Sharifi, M. (2021), "An efficient imperialist competitive algorithm with likelihood assimilation for topology, shape and sizing optimization of truss structures", Appl. Math. Model., 93, 1-27. https://doi.org/10.1016/j.apm.2020.11.044 
  11. Dogan, E. and Saka, M.P. (2012), "Optimum design of unbraced steel frames to LRFD-AISC using particle swarm optimization", Adv. Eng. Softw., 46, 27-34. https://doi.org/10.1016/j.advengsoft.2011.05.008 
  12. Duan, L., Xu, Z., Xu, W., Zhang, X., Du, Z., Liu, X. and Jiang, H. (2023), "Subdomain hybrid cellular automata method for material optimization of thin-walled frame structure under transverse impact", Int. J. Impact Eng., 174, 104524. https://doi.org/10.1016/j.ijimpeng.2023.104524. 
  13. Faramarzi, A. and Afshar, M.H. (2012), "Application of cellular automata to size and topology optimization of truss structures", Sci. Iran., 19, 373-380. https://doi.org/10.1016/j.scient.2012.04.009 
  14. Ghasemi, M.R., Ghasri, M. and Salarnia A. (2022), "Soccer league optimization-based championship algorithm (SLOCA): A fast novel meta-heuristic technique for optimization problems", Adv. Comput. Des., 7(4), 297-319. https://doi.org/10.12989/acd.2022.7.4.297. 
  15. Hasancebi, O. (2008), "Adaptive evolution strategies in structural optimization: Enhancing their computational performance with applications to large-scale structures", Comput. Struct., 86, 119-132. https://doi.org/10.1016/j.compstruc.2007.05.012 
  16. Hasancebi, O., C arbas, S., Dogan, E., Erdal, F. and Saka, M.P. (2009), "Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures", Comput. Struct., 87, 284-302. https://doi.org/10.1016/j.compstruc.2009.01.002 
  17. Hoekstra, A.G., Kroc, J. and Sloot, P.M.A. (2010), "Simulating Complex Systems by Cellular Automata", Springer, Berlin. 
  18. Kaveh, A., Eskandari, A. and Movasat, M. (2023), "Buckling resistance prediction of high-strength steel columns using metaheuristic-trained artificial neural networks", Structures, 56, 104853. https://doi.org/10.1016/j.istruc.2023.07.043 
  19. Kaveh, A. and Zaerreza, A. (2022), "Reliability-based design optimization of the frame structures using the force method and SORA-DM framework", Structures, 45, 814-827. https://doi.org/10.1016/j.istruc.2022.09.057 
  20. Kirkpatrick, S., Gerlatt, C.D. and Vecchi, M.P. (1983), "Optimization by simulated annealing", Science., 220, 671-680. https://doi.org/10.1126/science.220.4598.671 
  21. Liu, C., Zhang, F., Zhang, H., Shi, Z. and Zhu, H. (2023), "Optimization of assembly sequence of building components based on simulated annealing genetic algorithm", Alexandria Eng. J., 62, 257-268. https://doi.org/10.1016/j.aej.2022.07.025 
  22. Mashayekhi, M., Fadaee, M.J., Salajegheh, J. and Salajegheh, E. (2011), "Topology optimization of double-layer grids for earthquake loads using a two-stage ESO-ACO method", Int. J. Optim. Civ. Eng., 1, 211-232. 
  23. Mashayekhi, A., Mashayekhi, M. and Siciliano, B. (2023), "Identification and optimization of the operator's hand and a haptic device dynamic, using artificial intelligence methods", Int. J. Dyn. Control, https://doi.org/10.1007/s40435-023-01165-x. 
  24. Mashayekhi, M., Salajegheh, E., Salajegheh, J. and Fadaee, M.J. (2012), "Reliability-based topology optimization of double-layer grids using a two-stage optimization method", Struct. Multidiscipl. Opt., 45, 815-833. https://doi.org/10.1007/s00158-011-0744-6 
  25. Mashayekhi, M., Salajegheh, E. and Dehghani, M. (2015), "A new hybrid algorithm for topology optimization of double-layer grids", Int. J. Optim. Civ. Eng., 1(3), 353-374. 
  26. Mashayekhi, M., Salajegheh, E. and Dehghani, M. (2016), "Topology optimization of double and triple layer grid structures using a modified gravitational harmony search algorithm with efficient member grouping strategy", Comput. Struct., 172, 40-58. https://doi.org/10.1016/j.compstruc.2016.05.008 
  27. Mashayekhi, M. and Yousefi, R. (2021), "Topology and size optimization of truss structures using an improved crow search algorithm", Struct. Eng. Mech., 77(6), 779-795. https://doi.org/10.12989/sem.2021.77.6.779 
  28. Mohammadnejad, M. and Haji Kazemi, H. (2022), "Optimization of lateral resisting system of framed tubes combined with outrigger and belt truss", Adv. Comput. Des., 7(1), 19-35. https://doi.org/10.12989/acd.2022.7.1.019. 
  29. Mozafari, H., Ayob, A. and Kamali, F. (2012), "Optimization of functional graded plates for buckling load by using imperialist competitive algorithm", Proced. Technol., 1, 144-152. https://doi.org/10.1016/j.protcy.2012.02.028 
  30. Nabil, B., Khaled, B. and Mohamed, B. (2023), "Optimization of productivity in the rehabilitation of building linked to BIM", Adv. Comput. Des., 8(2), 179-190. https://doi.org/10.12989/acd.2023.8.2.179. 
  31. Neumann, J.V. (1966). "Theory of self-reproducing automata", University of Illinois Press. 
  32. Rajasekaran, S. (2001), "Optimization of large scale three dimensional reticulated structures using cellular genetics and neural networks", Int. J. Space Struct., 16, 315-324. https://doi.org/10.1260/026635101760832244 
  33. Rettl, M., Pletz, M. and Schuecker, C. (2023), "Evaluation of combinatorial algorithms for optimizing highly nonlinear structural problems", Mater. Des., https://doi.org/10.1016/j.matdes.2023.111958. https://doi.org/10.1016/j.matdes.2023.111958 
  34. Sonmez, M. (2011), "Discrete optimum design of truss structures using artificial bee colony algorithm", Struct. Multidiscipl. Opt., 43, 85-97. https://doi.org/10.1007/s00158-010-0551-5 
  35. Ulam, S. (1952), "Random processes and transformations", Proceedings of the International Congress of Mathematics, 2, 85-87. 
  36. Vasile, A., Coropetchi, I.C., Sorohan, S., Picu, C.R. and Constantinescu, D.M. (2022), "A simulated annealing algorithm for stiffness optimization", Procedia Structural Integrity, 37, 857-864.
  37. Zhang, X., Wang, D., Huang, B., Wang, S., Zhang, Z., Li, S., Xie, C., Kong, D. (2023), "A dynamic-static coupling topology optimization method based on hybrid cellular automata", Structures., 50, 1573-1583. https://doi.org/10.1016/j.istruc.2023.02.120