Capacity controlled search: A new and efficient design-driven method for discrete size optimization of steel frames

Date

2023-01-15

Author

Eser, Hasan
Hasançebi, Oğuzhan

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This paper presents a new and efficient design-driven method, called the capacity controlled search (CCS) algorithm, which is developed to handle sizing optimization of especially large-scale steel frames under multiple strength and displacement constraints. The CCS algorithm implements an intelligent and probabilistic search strategy, where the maximum demand-to-capacity ratios (DCRs) calculated for member groups are used to guide the search process for a rapid convergence to the optimum solution. The principle of virtual work or similar approaches that are commonly implemented by other design-driven methods are avoided in formulations of the CSS algorithm to make the method as simple and general as possible. The numerical performance of the proposed algorithm has been tested and verified on four steel frame design examples chosen from the literature. It is noted that the CCS algorithm produces the best-known solutions of these design examples in the literature until now. A statistical treatment of the independent runs performed with the CCS algorithm verifies robustness and reliability of the method.

Subject Keywords

Capacity controlled search algorithm, Design-driven search methods, Discrete sizing optimization, Steel frames, Structural optimization

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85141456080&origin=inward
https://hdl.handle.net/11511/101660

Journal

Computers and Structures

DOI

https://doi.org/10.1016/j.compstruc.2022.106937

Collections

Department of Civil Engineering, Article

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Citation Formats

H. Eser and O. Hasançebi, “Capacity controlled search: A new and efficient design-driven method for discrete size optimization of steel frames,” Computers and Structures, vol. 275, pp. 0–0, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85141456080&origin=inward.