A Qualitative Review of Two Evolutionary Algorithms Inspired by Heuristic Population Based Search Methods: GA & PSO

Abstract

PSO is relatively recent Evolutionary computational technique which is inspired by swarming behavior of biological populations. PSO and GA are resembles in sense that both are heuristic population based search methods. In other words both starts from random variable and reach to a final desired solutions without any user input. GA has been utilizing in many research and in many form because its easiness in implementation and ability to solve highly complex non-linear engineering problems but it is costly. This paper claims that PSO is more effective then GA while it is very recent but in sense of implementation, in solving complex problems it is more efficient.