Resizing technique-based hybrid genetic algorithm for optimal drift design of multistory steel frame buildings

Hyo Seon Park, Eunmi Kwon, Yousok Kim, Se Woon Choi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.

Original languageEnglish
Article number237131
JournalMathematical Problems in Engineering
Volume2014
DOIs
Publication statusPublished - 2014 Jan 1

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Hybrid Genetic Algorithm
Steel
Genetic algorithms
Genetic Algorithm
Structural Optimization
Speed of Convergence
Structural Analysis
Convergence Properties
Optimization Methods
Structural optimization
Design
Buildings
Evaluate
Structural analysis

All Science Journal Classification (ASJC) codes

  • Mathematics(all)
  • Engineering(all)

Cite this

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abstract = "Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.",
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Resizing technique-based hybrid genetic algorithm for optimal drift design of multistory steel frame buildings. / Park, Hyo Seon; Kwon, Eunmi; Kim, Yousok; Choi, Se Woon.

In: Mathematical Problems in Engineering, Vol. 2014, 237131, 01.01.2014.

Research output: Contribution to journalArticle

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