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Weight Optimization of Square Hollow Steel Trusses Using Genetic Algorithm

Ede, A. N. and Oshokoya, O.O and Oluwafemi, J.O and Oyebisi, S.O and Olofinnade, O. M. and Akpabot, Akpabot Ifiok Weight Optimization of Square Hollow Steel Trusses Using Genetic Algorithm. In: International Conference on Engineering for a Sustainable World (ICESW).

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Abstract

Conceptual design in structural engineering entails a large amount of trial and errors or extensive expertise to obtain the most economical and functional design solutions for large engineering projects. In this paper a modern optimization technique called Genetic algorithm, adopting its concept from genetic evolution is used to optimize the shape, size and topology of a plane truss structure with the aim of minimizing the total weight of the truss. A genetic algorithm developed in MATLAB was implemented in this paper to optimize the weight of plane truss structures. The objective function of the optimization problem is subjected to constraints such as stress limits, buckling constraints, tension and compression capacity according to British steel design code BS 5950. The plane trusses which were subject to point loads were tested in the genetic algorithm, the resulting optimized truss structures were then subject to real life loading to determine their feasibility to withstand real life loading. The optimized trusses presented by the algorithm were modelled in a structural analysis and design software called SAP 2000, where they were subjected to dead and live loads. After design the weight saving discovered between the original trusses and the optimized version was between 37 - 47%. The results show that the genetic algorithm implemented in this study is useful in optimizing the weight of a plane truss structure.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: UNSPECIFIED
Depositing User: Dr Oluwarotimi Michael Olofinnade
Date Deposited: 12 Sep 2018 12:03
Last Modified: 12 Sep 2018 12:03
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/11546

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