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

Davoud Safari, Alireza Maheri, Mahmoud Maheri

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1232-1243
JournalJournal of Constructional Steel Research
Issue number8
Publication statusPublished - 27 Mar 2011


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