Buckling optimization of laminated composite plates using genetic algorithm and generalized pattern search algorithm

In this paper, genetic algorithm and generalized pattern search algorithm are used for optimal stacking sequence of a composite panel, which is simply supported on four sides and is subject to biaxial in-plane compressive loads. The problem has several global optimum configurations in the vicinity o...

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Bibliographic Details
Published in:Structural and multidisciplinary optimization Vol. 39; no. 5; pp. 477 - 486
Main Authors: Karakaya, Şükrü, Soykasap, Ömer
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer-Verlag 01.11.2009
Springer Nature B.V
Subjects:
Aspect ratio
Buckling
Composite structures
Computational Mathematics and Numerical Analysis
Engineering
Engineering Design
Genetic algorithms
Graphite fiber reinforced plastics
Graphite-epoxy composites
Optimization
Pattern search
Plates (structural members)
Production scheduling
Research Paper
Search algorithms
Stacking sequence (composite materials)
Theoretical and Applied Mechanics
Genetic algorithm
Composites
Optimization
ISSN:1615-147X, 1615-1488
Online Access:Get full text
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Summary:In this paper, genetic algorithm and generalized pattern search algorithm are used for optimal stacking sequence of a composite panel, which is simply supported on four sides and is subject to biaxial in-plane compressive loads. The problem has several global optimum configurations in the vicinity of local optima. The composite plate under consideration is 64-ply laminate made of graphite/epoxy. The laminate is taken to be symmetric and balanced, comprised of two-ply stacks with discrete fiber angles of 0 2 , ± 45, 90 2 in the laminate sequence. The critical buckling loads are maximized for several combinations of load case and plate aspect ratio, and are compared with published results. Performance of both algorithms is compared in terms of capability of identifying global optima. It is found that genetic algorithm is efficient for problems with global optima.
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ISSN:1615-147X
1615-1488
DOI:10.1007/s00158-008-0344-2