Session Dates
24 Aug 2012 - 25 Aug 2012
Keywords and Phrases
portal frame, cold-formed steel, optimization, genetic algorithm
Abstract
The design optimization of cold-formed steel portal frame buildings is considered in this paper. The real-coded genetic algorithm (GA) optimizer proposed considers both building’s topology (i.e. frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables that are optimized. Previous GAs in the literature were characterized by poor convergence including slow progress that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Through a benchmark example, it is shown that the efficient GA proposed generates the optimal solution more consistently with three times faster of the computation time in comparison to the conventional GA.
Department(s)
Civil, Architectural and Environmental Engineering
Research Center/Lab(s)
Wei-Wen Yu Center for Cold-Formed Steel Structures
Meeting Name
21st International Specialty Conference on Cold-Formed Steel Structures
Publisher
Missouri University of Science and Technology
Document Version
Final Version
Rights
© 2012 Missouri University of Science and Technology, All rights reserved.
Document Type
Article - Conference proceedings
File Type
text
Language
English
Recommended Citation
Phan, Duoc T.; Lim, James B. P.; Tanyimboh, Tiku T.; and Sha, Wei, "An Efficient Genetic Algorithm for the Design Optimization of Cold-formed Steel Portal Frame Buildings" (2012). CCFSS Proceedings of International Specialty Conference on Cold-Formed Steel Structures (1971 - 2018). 1.
https://scholarsmine.mst.edu/isccss/21iccfss/21iccfss-session8/1
An Efficient Genetic Algorithm for the Design Optimization of Cold-formed Steel Portal Frame Buildings
The design optimization of cold-formed steel portal frame buildings is considered in this paper. The real-coded genetic algorithm (GA) optimizer proposed considers both building’s topology (i.e. frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables that are optimized. Previous GAs in the literature were characterized by poor convergence including slow progress that usually results in excessive computation times and/or frequent failure to achieve an optimal or near-optimal solution. This is the main issue addressed in this paper. In an effort to improve the performance of the conventional GA, a niching strategy is presented that is an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Through a benchmark example, it is shown that the efficient GA proposed generates the optimal solution more consistently with three times faster of the computation time in comparison to the conventional GA.
