Genetic Algorithms with Local Improvement for Composite Laminate Design

Kogiso, N. and Watson, Layne T. and Gurdal, Z. and Haftka, Robert T. (1993) Genetic Algorithms with Local Improvement for Composite Laminate Design. Technical Report TR-93-17, Computer Science, Virginia Polytechnic Institute and State University.

Abstract

This paper describes the application of a genetic algorithm to the stacking sequence optimization of a composite laminate plate for buckling load maximization. Two approaches for reducing the number of analyses are 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 improvements 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.