The Effect of Rearrangement of the Most Incompatible Particle on Increase of Convergence Speed of PSO

Abstract

This article presents a new method for increasing the speed of Particle Swarm Optimization (PSO) method. The particle swarm is an optimization method that was inspired by collective movement of birds and fish looking for food. This method is composed of a group of particles: each particle tries to move in one direction that the best individual and best group of particles occur in that direction. Different articles tried to expand PSO so that global optimization is gained in less time. One of the problems of this model that occurs in most cases is falling of particles in local optimum. By finding the most incompatible particle and its rearrangement in the searching space, we increase convergence speed in some considered methods. Different tests of this method in standard searching space demonstrated that this method takes account of suitable function of increasing the convergece speed of particles.

DOI:http://dx.doi.org/10.11591/ijece.v3i2.2026