An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings

DT Phan, James B.P. Lim, Tiku Tanyimboh, W Sha

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. 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 shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.
LanguageEnglish
Pages519-538
Number of pages10
JournalSteel and Composite Structures
Volume15
Issue number5
Publication statusPublished - Nov 2013

Fingerprint

Steel
Genetic algorithms
Topology
Structural members
Costs
Design optimization

Keywords

  • optimization
  • cold-formed steel
  • portal frames
  • real-coded genetic algorithm

Cite this

Phan, DT ; Lim, James B.P. ; Tanyimboh, Tiku ; Sha, W. / An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings. In: Steel and Composite Structures. 2013 ; Vol. 15, No. 5. pp. 519-538.
@article{56499f5b0de34b7591a3d624f9696d70,
title = "An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings",
abstract = "The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. 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 nichingstrategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.",
keywords = "optimization, cold-formed steel, portal frames, real-coded genetic algorithm",
author = "DT Phan and Lim, {James B.P.} and Tiku Tanyimboh and W Sha",
year = "2013",
month = "11",
language = "English",
volume = "15",
pages = "519--538",
journal = "Steel and Composite Structures",
issn = "1229-9367",
publisher = "Techno Press",
number = "5",

}

An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings. / Phan, DT; Lim, James B.P.; Tanyimboh, Tiku; Sha, W.

In: Steel and Composite Structures, Vol. 15, No. 5, 11.2013, p. 519-538.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An efficient genetic algorithm for the design optimization of cold-formed steel portal frame buildings

AU - Phan, DT

AU - Lim, James B.P.

AU - Tanyimboh, Tiku

AU - Sha, W

PY - 2013/11

Y1 - 2013/11

N2 - The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. 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 nichingstrategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.

AB - The design optimization of a cold-formed steel portal frame building is considered in this paper. The proposed genetic algorithm (GA) optimizer considers both topology (i.e., frame spacing and pitch) and cross-sectional sizes of the main structural members as the decision variables. 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 nichingstrategy is presented that is shown to be an effective means of enhancing the dissimilarity of the solutions in each generation of the GA. Thus, population diversity is maintained and premature convergence is reduced significantly. Through benchmark examples, it is shown that the efficient GA proposed generates optimal solutions more consistently. A parametric study was carried out, and the results included. They show significant variation in the optimal topology in terms of pitch and frame spacing for a range of typical column heights. They also show that the optimized design achieved large savings based on the cost of the main structural elements; the inclusion of knee braces at the eaves yield further savings in cost, that are significant.

KW - optimization

KW - cold-formed steel

KW - portal frames

KW - real-coded genetic algorithm

UR - http://technopress.kaist.ac.kr/?journal=scs

M3 - Article

VL - 15

SP - 519

EP - 538

JO - Steel and Composite Structures

T2 - Steel and Composite Structures

JF - Steel and Composite Structures

SN - 1229-9367

IS - 5

ER -