An Efficient Global Optimization Algorithm:Empirical Genetic Algorithm

It is necessary to obtain corresponcling solutions to evaluating the fitness of all individuals of every generation of the population and to analyze the solutions by using Genetic Algorithm. When the scale of problem is large, the calculation of genetic algorithm will be so enormous that it ean not be used in practice. However, a new method called empirical genetic algorithm is proposed in the paper. It decrease the number to analyze the solution and increase the efficiency of the genetic algorithm, in which the fitness of most individuals of every generation of the population are estimated by the empirical Neural Network. The calculation results from six classical test functions show that the method is efficient.