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Shape and Cross-Section Optimization of Spatial Grid Structures Using Genetic Algorithm

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Abstract:

The optimization of the structures is difficult because the variables have different physical property or different quantitative attribute. The shape and cross-section optimization of spatial grid structures is performed by an improved genetic algorithm. The constraint conditions are composed of the structural deformation, the stability of the compressive members, the slender ratios, and etc. The treatment of the constraint conditions and the optimization function gives an unconstrained analytic function by adopting Lagrange multipliers. The method enhances the running efficiency of the genetic algorithm. The programme for structural optimization containing the mixed codes of continuous real variables, discontinuous real variables, and integer variables is coded by using MATLAB Toolbox functions for genetic algorithm. The analysis of examples shows that the programme is reliable, and the convergence of the algorithm is fast as well.

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Periodical:

Advanced Materials Research (Volumes 479-481)

Pages:

1463-1467

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.479-481.1463

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Online since:

February 2012

Authors:

Jian Chun Xiao, Jing Chen, Qi Li, Shao Quan Xia

Keywords:

Genetic Algorithm (GA), Optimization, Spatial Grid Structure

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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References

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