M. R. Ghasemi and A. Ehsani
Multiobjective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid NeuroGA Algorithm
1 - 6
2007
1
1
International Journal of Civil and Environmental Engineering
https://publications.waset.org/pdf/9507
https://publications.waset.org/vol/1
World Academy of Science, Engineering and Technology
In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the TsaiHill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuroGA environment, and the procedure will be carried out until a predicted optimum solution is achieved.
Open Science Index 1, 2007