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A comparative analysis of ant colony and genetic algorithm optimization to select optimal arrangement of viscous damper in steel frame

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Abstract

Natural phenomena-based optimization methods have gained recognition in recent years due to their lack of heavy mathematical calculations, independence from primary selection points, and general optimization capabilities. In this study, two optimization methods inspired by nature have been used to determine the optimal arrangement of viscous dampers, namely genetic algorithms and ant communities. The purpose of this article is to investigate the effects of viscous dampers on the behavior of a two-dimensional steel frame. Due to the aim of this study being to investigate the seismic behavior of the structure, a dynamic analysis of time history has been performed. The dynamic frame analysis and optimization algorithms are implemented using the MATLAB programming language. It is shown in this study that dampers affect the behavior of the structure, that optimizing damper arrangement influences the final response of the structure, and that the strength and weaknesses of each optimization method are demonstrated.

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References

  • Akcelyan, S., Lignos, D.G., Hikino, T.: Adaptive numerical method algorithms for nonlinear viscous and bilinear oil damper models subjected to dynamic loading. Soil Dyn. Earthq. Eng. 113, 488–502 (2018)

    Article  Google Scholar 

  • Almufti, S., Marqas, R., Ashqi, V.: Taxonomy of bio-inspired optimization algorithms. J. Adv. Comput. Sci. Technol. 8, 23 (2019)

    Article  Google Scholar 

  • Asghari, A., Saharkhizan, S.: Seismic design and performance evaluation of steel frames with knee-element connections. J. Constr. Steel Res. 154, 161–176 (2019)

    Article  Google Scholar 

  • Azam, R., Riaz, M.R., Farooq, M.U., Ali, F., Mohsan, M., Deifalla, A.F., et al.: Optimization-based economical flexural design of singly reinforced concrete beams: a parametric study. Materials (Basel) 15, 3223 (2022)

    Article  CAS  PubMed  Google Scholar 

  • Bekdaş, G., Nigdeli, S.M., Kayabekir, A.E., Yang, X.-S.: Optimization in civil engineering and metaheuristic algorithms: a review of state-of-the-art developments. In: Computational Intelligence, Optimization and Inverse Problems with Applications in Engineering, pp. 111–137. Springer, Cham (2019)

  • do Amaral, J.V.S., Montevechi, J.A.B., de Carvalho Miranda, R., de Sousa Junior, W.T.: Metamodel-based simulation optimization: a systematic literature review. Simul. Model. Pract. Theory 114, 102403 (2022)

  • Dorigo, M., Blum, C.: Ant colony optimization theory: a survey. Theor. Comput. Sci. 344, 243–278 (2005)

    Article  Google Scholar 

  • Dorigo, M., Socha, K.: An introduction to ant colony optimization. In: Handbook of Approximation Algorithms and Metaheuristics, pp. 395–408. Chapman and Hall/CRC, Boca Raton (2018)

  • Dorigo, M., Stützle, T.: Ant colony optimization: overview and recent advances. In: Handbook of Metaheuristics. International Series in Operations Research & Management Science. Springer, Cham (2019)

  • Eslami, E.: Analytical study of deep learning methods for road condition assessment. Electronic Theses and Dissertations (2022)

  • Esmaeili, J., Andalibi, K., Gencel, O.: Mechanical characteristics of experimental multi-scale steel fiber reinforced polymer concrete and optimization by Taguchi methods. Constr. Build. Mater. 313, 125500 (2021)

    Article  CAS  Google Scholar 

  • Gen, M., Cheng, R.: Genetic Algorithms and Engineering Optimization, vol. 7. Wiley, New York (1999)

    Book  Google Scholar 

  • Guo, K., Zhang, L.: Multi-objective optimization for improved project management: current status and future directions. Autom. Constr. 139, 104256 (2022)

    Article  Google Scholar 

  • Kaidi, W., Khishe, M., Mohammadi, M.: Dynamic levy flight chimp optimization. Knowl. Based Syst. 235, 107625 (2022)

    Article  Google Scholar 

  • Katoch, S., Chauhan, S.S., Kumar, V.: A review on genetic algorithm: past, present, and future. Multimedia Tools Appl. 80, 8091–8126 (2021)

    Article  Google Scholar 

  • Kaveh, A., Eslamlou, A.D.: Metaheuristic Optimization Algorithms in Civil Engineering: New Applications. Springer, Cham (2020)

    Book  Google Scholar 

  • Kaveh, A., Ghafari, M.H., Gholipour, Y.: Optimum seismic design of steel frames considering the connection types. J. Constr. Steel Res. 130, 79–87 (2017)

    Article  Google Scholar 

  • Khajehzadeh, M., Keawsawasvong, S., Sarir, P., Khailany, D.K.: Seismic analysis of earth slope using a novel sequential hybrid optimization algorithm. Period Polytech. Civ. Eng. 66, 355–366 (2022)

    Google Scholar 

  • Lignos, D.: Sidesway Collapse of Deteriorating Structural Systems Under Seismic Excitations. Stanford University, Stanford (2008)

    Google Scholar 

  • Maleki, V.A., Mohammadi, N.: Buckling analysis of cracked functionally graded material column with piezoelectric patches. Smart Mater. Struct. 26, 35031 (2017)

    Article  Google Scholar 

  • Mei, L., Wang, Q.: Structural optimization in civil engineering: a literature review. Buildings 11, 66 (2021)

    Article  Google Scholar 

  • Sekulovic, M., Salatic, R., Nefovska, M.: Dynamic analysis of steel frames with flexible connections. Comput. Struct. 80, 935–955 (2002)

    Article  Google Scholar 

  • Symans, M., Constantinou, M.: Passive fluid viscous damping systems for seismic energy dissipation. ISET J. Earthq. Technol. 35(4), 185–206 (1998)

    Google Scholar 

  • Xu, Q., Mao, J., Jin, Z.: Simulated annealing-based ant colony algorithm for tugboat scheduling optimization. Math. Probl. Eng. 2012, Article ID 246978 (2012)

Download references

Acknowledgements

This work was supported by the Research project on teaching reform of Higher Vocational Education of Chongqing Municipal Education Commission of China (Grant No. Z213067).

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Authors and Affiliations

  1. Architecture and Materials College, Chongqing College of Electronic Engineering, Chongqing, 401331, China

    Huijing Li

  2. Artificial Intelligence and Big Data College, Chongqing College of Electronic Engineering, Chongqing, 401331, China

    Li Li

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  1. Huijing Li
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  2. Li Li
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Contributions

HL: Writing—original draft preparation, conceptualization, supervision, project administration. LL: Methodology, software, validation, formal analysis.

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Correspondence to Huijing Li.

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The authors declare no competing interests.

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Communicated by Daniel Pellegrino

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Li, H., Li, L. A comparative analysis of ant colony and genetic algorithm optimization to select optimal arrangement of viscous damper in steel frame. Proc.Indian Natl. Sci. Acad. 90, 75–81 (2024). https://doi.org/10.1007/s43538-023-00220-7

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  • DOI: https://doi.org/10.1007/s43538-023-00220-7

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