A Comparative Performance of Swarm Intelligence Optimization Method and Evolutionary Optimization Method on Some Noisy Numerical Benchmark Test Problems

Abstract

Recently many algorithms have been developed which mimics the natural procedure better known as Evolutionary Algorithm and claims to perform better than others. The objective of this paper is to test the performance of Genetic algorithm and Repulsive Particle Swarm method on some benchmark functions. Since GA(Genetic Algorithm) mimics the nature and (RPS) exploits the swarm intelligence, it will be interesting to see the performance of these two methods on the certain test functions. A brief idea of these functions are given in this section are as follows. These functions are also represented by graph to facilitate conceptualization of the nature of these functions by visual means.