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Upper bound strategy for metaheuristic based design optimization of steel frames
Date
2013-03-01
Author
Kazemzadeh Azad, Saeid
Hasançebi, Oğuzhan
Kazemzadeh Azad, Sina
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Optimum design of structural systems based on metaheuristic algorithms suffers from enormously time-consuming structural analyses to locate a reasonable design. In this paper an upper bound strategy (UBS) is proposed for reducing the total number of structural analyses in metaheuristic based design optimization of steel frame structures. The well-known big bang-big crunch algorithm as well as its two enhanced variants are adopted as typical metaheuristic algorithms to evaluate the effect of the UBS on computational efficiency of these techniques. The numerical results reveal that the UBS can significantly lessen the total computational cost in metaheuristic based design optimization of steel frames.
Subject Keywords
Structural optimization
,
Metaheuristic search techniques
,
Big bang-big crunch algorithm
,
Upper bound strategy
,
Steel frames
,
AISC-LRFD provisions
URI
https://hdl.handle.net/11511/46208
Journal
ADVANCES IN ENGINEERING SOFTWARE
DOI
https://doi.org/10.1016/j.advengsoft.2012.11.016
Collections
Department of Civil Engineering, Article
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S. Kazemzadeh Azad, O. Hasançebi, and S. Kazemzadeh Azad, “Upper bound strategy for metaheuristic based design optimization of steel frames,”
ADVANCES IN ENGINEERING SOFTWARE
, pp. 19–32, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46208.