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There are some methods designed to find suitable designs using techniques that avoid the use of the pursuit of gradients or almost gradients. A system that either uses random variations in design variables or avoids direct variations in design variables by the use of learning networks supplements the use of directional searches. We have selected the genetic algorithm (GA) as a representative in the first category, RAT (GRS), and we have selected the Artificial NERN (ANN) as a regular illustration in the second category, network-based learning methods.