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2024 | Vol. 70, nr 4 | 57--70
Tytuł artykułu

The application of ICPA optimization algorithm in multi-objective optimization structural design of prefabricated buildings

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EN
With the prefabricated buildings developing, traditional architectural design methods can no longer meet the requirements of efficient, green, and sustainable development. In view of this, based on the analysis of the framework structure of the cyclical parthenogenesis algorithm, the study introduced chaotic optimization algorithm for improvement. And the improved new algorithm was applied to multi-objective problems in the optimization design of prefabricated building structures. Finally, a novel structural design optimization model was proposed. These experiments confirmed that the improved algorithm had the least 160 iterations and 17 optimal solutions, which was an increase of 15 compared to traditional aphid algorithms. Two function solutions of this new structural design optimization model were both between -0:5 and 0.5, with relatively smaller values. In addition, this model could effectively optimize and transform physical buildings, increasing their structural stability by 2.43%, increasing their structural quality coefficient by 4.49%, reducing vibration cycles by 0.06%, and reducing inter story displacement angles by 0.04%. In summary, the improved cyclical parthenogenesis algorithm has good performance in solving multi-objective problems in prefabricated structures, and can quickly and accurately find the global optimal solution. This study aims to provide guidance for the prefabricated building structure design.
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57--70
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Bibliogr. 16 poz., il., tab.
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autor
Bibliografia
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  • [10] A. Kaveh and M.R. Seddighian, “Domain decomposition of finite element models utilizing eight meta-heuristic algorithms: a comparative study”, Mechanics Based Design of Structures and Machines, vol. 50, no. 8, pp. 2616-2634, 2022, doi: 10.1080/15397734.2020.1781655.
  • [11] R. Sun, E. Zhang, D. Mu, S. Ji, Z. Zhang, H. Liu, and Z. Fu, “Optimization of the 3D point cloud registration algorithm based on FPFH features”, Applied Sciences, vol. 13, no. 5, art. no. 3096, 2023, doi: 10.3390/app13053096.
  • [12] X. Shen, S. Aliko, Y. Han, J. Skipper, and C. Peng, “Finding core-periphery structures with node influences”, IEEE Transactions on Network Science and Engineering, vol. 9, no. 2, pp. 875-887, 2022, doi: 10.1109/TNSE.2021.3138436.
  • [13] B. Nan, Y. Bai, and Y. Wu, “Multi-objective optimization of spatially truss structures based on node movement”, Applied Sciences, vol. 10, no. 6, art. no. 1964, 2020, doi: 10.3390/app10061964.
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Typ dokumentu
Bibliografia
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