Genetic algorithms (GA) are an adaptation procedure based on the mechanics of natural genetics and natural selection. They are designed to perform search procedures of an artificial system by emulating the evolution process (Darwin’s evolutionary principle) observed in nature and biological organisms. The evolution process is based on the preferential survival and reproduction of the fittest member of a population with direct inheritance of genetic information from parents to offspring and the occasional mutation of genes. The principal advantage of GA's is their inherent ability to intelligently explore the solution space from many different points simultaneously enabling higher probability for locating global optimum without having to analyze all possible solutions available and without requiring derivatives (or numerical approximations) or other auxiliary knowledge.