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

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

134
views

0
downloads

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

Suggestions

OpenMETU
Core

Discrete sizing optimization of steel trusses under multiple displacement constraints and load cases using guided stochastic search technique Azad, S. Kazemzadeh; Hasançebi, Oğuzhan (2015-08-01) The guided stochastic search (GSS) is a computationally efficient design optimization technique, which is originally developed for discrete sizing optimization problems of steel trusses with a single displacement constraint under a single load case. The present study aims to investigate the GSS in a more general class of truss sizing optimization problems subject to multiple displacement constraints and load cases. To this end, enhancements of the GSS are proposed in the form of two alternative approaches t...
Layout optimization of trusses using simulated annealing Hasançebi, Oğuzhan (2000-09-08) This paper addresses to the development of a simulated annealing (SA) based solution algorithm which is automated to achieve the simultaneous optimum design of truss type structures with respect to size, shape and topology design variables. The proposed algorithm is designed in such a way that together with applicability to practical design problems, it is also aimed at producing efficient and improved design solutions for the problems of interest. From the practicality point of view, the task is chosen as ...
Computationally efficient discrete sizing of steel frames via guided stochastic search heuristic Azad, S. Kazemzadeh; Hasançebi, Oğuzhan (2015-08-01) Recently a design-driven heuristic approach named guided stochastic search (GSS) technique has been developed by the authors as a computationally efficient method for discrete sizing optimization of steel trusses. In this study, an extension and reformulation of the GSS technique are proposed for its application to problems from discrete sizing optimization of steel frames. In the GSS, the well-known principle of virtual work as well as the information attained in the structural analysis and design stages a...
Harmony search algorithms in structural engineering Saka, M.P.; Aydogdu, I.; Hasançebi, Oğuzhan; Geem, Z.W. (2011-08-08) Harmony search method is widely applied in structural design optimization since its emergence. These applications have shown that harmony search algorithm is robust, effective and reliable optimization method. Within recent years several enhancements are suggested to improve the performance of the algorithm. Among these Mandavi has presented two versions of harmony search methods. He named these as improved harmony search method and global best harmony search method. Saka and Hasancebi (2009) have suggested...
Improving the performance of simulated annealing in structural optimization Hasançebi, Oğuzhan; Saka, Mehmet Polat (2010-03-01) This study aims at improving the performance of simulated annealing (SA) search technique in real-size structural optimization applications with practical design considerations. It is noted that a standard SA algorithm usually fails to produce acceptable solutions to such problems associated with its poor convergence characteristics and incongruity with theoretical considerations. In the paper novel approaches are developed and incorporated into the standard SA algorithm to eliminate the observed drawbacks ...

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.