Genetic optimization of stiffened plates and shells

This work gives two examples of application of stochastic techniques for the optimization of stiʹened plates or shells. The research strategy consists in substituting, for 8nite-element calculations in the optimization process, an approximate response of a neural network, or an approximate response from the Ritz method. More precisely, the paper describes the use of a backpropagation neural network or the Ritz method in creating function approximations for use in computationally intensive design optimization based on genetic algorithms. Two examples of applications are presented; the 8rst one deals with the optimization of stiʹeners on a plate by varying their positions, while having well-de8ned dimensions; the second example deals with the optimization of a thin shell subject to buckling