An Overview on Particle Swarm Optimization: Basic Concepts and Modified Variants

S. D. Chavan, Nisha P. Adgokar

Abstract: Particle Swarm Optimization (PSO) is stochastic optimization algorithm inspired by behavior of bird swarm searching for the food. PSO is a new, powerful intelligent swarm intelligence based algorithm used for finding optimum solution for complex problems. It can be modified to lots of other versions to increase speed of convergence and diversity. PSO variants are discovered to increase its performance and improve the ability to solve a wide range of optimization problems. In this paper, our focus is on classical PSO, its control parameters and modified versions.

Keywords: Particle Swarm Optimization PSO, Global Best PSO GBPSO, Decreasing Weight PSO DWPSO, Time-Varying Acceleration Coefficient PSO TVACPSO, Guaranteed Convergence PSO GCPSO, Adaptive PSO APSO, Hybrid PSO HPSO