A Function Optimization Problem of Evolutionary Programming in Genetic Algorithm

The significant category of Evolutionary algorithms is Evolutionary Programming in the applications of Genetic Algorithm. To seek out the solutions for function optimization problems are based only on mutation operators. This paper mainly focuses on calculating and evaluating the fitness by taking the best solution that is obtained from the population, after the crossover and mutations are performed. The mutation operation is based on the Cauchy distribution. In this paper we propose a function optimization technique of Evolutionary Programming. The solution selection mechanism used here to solve the problem will enhance the performance of the function optimization of Evolutionary Programming.