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Genetic algorithms with local improvement for composite laminate design


This paper describes the application of a genetic algorithm to the stacking sequence optimization of a laminated composite plate for buckling load maximization. Two approaches for reducing the number of analyses required by the genetic algorithm are described. First, a binary tree is used to store designs, affording an efficient way to retrieve them and thereby avoid repeated analyses of designs that appeared in previous generations. Second, a local improvement scheme based on approximations in terms of lamination parameters is introduced. Two lamination parameters are sufficient to define the flexural stiffness and hence the buckling load of a balanced, symmetrically laminated plate. Results were obtained for rectangular graphite-epoxy plates under biaxial in-plane loading. The proposed improvements are shown to reduce significantly the number of analyses required for the genetic optimization.

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Communicated by J. Sobieski

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Kogiso, N., Watson, L.T., Gürdal, Z. et al. Genetic algorithms with local improvement for composite laminate design. Structural Optimization 7, 207–218 (1994).

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  • Genetic Algorithm
  • Civil Engineer
  • Lamination
  • Load Maximization
  • Binary Tree