A Survey on Particle Swarm Optimization in Feature Selection

Particle swarm optimization is an evolutionary algorithm that depicts the movement of flock of birds in space in mathematical terms. In PSO we view each potential problem as a particle with certain velocity flying through a problem space just like a flock of bird. In the world of infinite data, the ability to handle imprecise and inconsistent information and to select important features from the data has become the important requirement of feature selection. PSO has come a long way since its beginning and has become an important tool for feature selection in numerous physical problems. In this paper we present a literary review of papers on PSO and chart its journey through inception and with implementing it in various physical problems. We will present a comparative table of implementation for PSO and review the success of PSO in various fields of science. This paper provides an incentive for the readers to join the PSO world.