Optimum design of steel frames using a multiple-deme GA with improved reproduction operators

D. Safari, Mahmoud R. Maheri*, Alireza Maheri

*Corresponding author for this work

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

In this paper, the performance of the genetic algorithm is improved by introducing some new crossover and mutation operators. The new operators are incorporated into a multiple-deme genetic algorithm in which population is divided into subpopulations and communication between different demes is established through migration of individuals, enhancing diversity and resulting in better solutions. This algorithm is applied to the minimum weight design of steel frames subjected to actual strength and ductility constraints of AISC-ASD specifications as well as other serviceability and constructability constraints. The efficiency of the proposed method is demonstrated through optimising two benchmark problems including a three-bay, three-storey steel frame and a five-bay, 22-storey special steel frame. Significant improvements in the optimum solutions are obtained with reduced number of finite element analyses, resulting in less computational effort. (C) 2011 Elsevier Ltd. All rights reserved.

Original languageEnglish
Pages (from-to)1232-1243
Number of pages12
JournalJournal of Constructional Steel Research
Volume67
Issue number8
DOIs
Publication statusPublished - Aug 2011

Keywords

  • Structural optimisation
  • Steel frames
  • Multiple-deme genetic algorithm
  • Modified crossover
  • Modified mutation
  • RESISTANCE FACTOR DESIGN
  • OF-THE-ART
  • GENETIC ALGORITHM
  • SEMIRIGID CONNECTIONS
  • SPACE FRAMES
  • EVOLUTIONARY COMPUTATION
  • TABU SEARCH
  • OPTIMIZATION
  • LOAD

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