We consider the Artificial Neural network as a black box. A black box with the ability of learning, that is modify its behaviour according to the set of training pairs (design variables) - (objective functions) that we have generated. Neural networks have also another important property. The property is called generalisation property. They can compute a good approximation of the objective functions given a design variables vector not belonging to the training set.