Computationally efficient discrete sizing of steel frames via guided stochastic search heuristic

Date

2015-08-01

Author

Azad, S. Kazemzadeh
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

155
views

0
downloads

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 are used together to guide the optimization process. A design wise strategy is employed in the technique where resizing of members is performed with respect to their role in satisfying strength and displacement constraints. The performance of the GSS is investigated through optimum design of four steel frame structures according to AISC-LRFD specifications. The numerical results obtained demonstrate that the GSS can be employed as a computationally efficient design optimization tool for practical sizing optimization of steel frames.

Subject Keywords

Sizing optimization, Discrete optimization, Steel frames, Heuristic approach, AISC-LRFD specifications, Principle of virtual work

URI

https://hdl.handle.net/11511/44252

Journal

COMPUTERS & STRUCTURES

DOI

https://doi.org/10.1016/j.compstruc.2015.04.009

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...
Guided stochastic search technique for discrete sizing optimization of steel trusses: A design-driven heuristic approach Azad, S. Kazemzadeh; Hasançebi, Oğuzhan; Saka, M. P. (Elsevier BV, 2014-04-01) This study presents a design-driven heuristic approach named guided stochastic search (GSS) technique for discrete sizing optimization of steel trusses. The method works on the basis of guiding the optimization process using the well-known principle of virtual work as well as the information collected during the structural analysis and design stages. The performance of the proposed technique is investigated through a benchmark truss instance as well as four real-size trusses sized for minimum weight accordi...
Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization Hasançebi, Oğuzhan (2015-07-01) In the present study a new metaheuristic algorithm called adaptive dimensional search (ADS) is proposed for discrete truss sizing optimization problems. The robustness of the ADS lies in the idea of updating search dimensionality ratio (SDR) parameter online during the search for a rapid and reliable convergence towards the optimum. In addition, several alternative stagnation-control strategies are integrated with the algorithm to escape from local optima, in which a limited uphill (non-improving) move is p...
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 ...
Capacity controlled search: A new and efficient design-driven method for discrete size optimization of steel frames Eser, Hasan; Hasançebi, Oğuzhan (2023-01-15) 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 prin...

Citation Formats

S. K. Azad and O. Hasançebi, “Computationally efficient discrete sizing of steel frames via guided stochastic search heuristic,” COMPUTERS & STRUCTURES, pp. 12–28, 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/44252.