Structural Optimization by Gradient-Based Neural Networks

In this chapter a neuro computing strategy is presented which combines data processing capabilities of neural networks and numerical structural optimization. In this strategy, an improved counter propagation neural network is used. Two artificial neural networks are trained, one for the constraints and the other for the gradients of the constraints and structural optimization is accomplished by using these nets. All required parameters such as weight matrices in the neural networks or the gradient computations are automated in this neuro-optimizer strategy.