title: Particle Swarm Optimization for Single Objective Continuous Space Problems: A Review.
abstract: This paper reviews recent studies on the Particle Swarm Optimization (PSO) algorithm. The review has been focused on high impact recent articles that have analyzed and/or modified PSO algorithms. This paper also presents some potential areas for future study.
authors.affiliation: Department of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia. Also with the Centre for Advanced Imaging (CAI), the University of Queensland, Brisbane, QLD 4067, Australia, and Complexica Pty Ltd, Adelaide, SA 5021, Australia. mrbonyadi@cs.adelaide.edu.au , rezabny@gmail.com.
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Bonyadi
authors.affiliation: Department of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia. Also with Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland, Polish-Japanese Institute of Information Technology, Warsaw, Poland, and Complexica Pty Ltd, Adelaide, SA 5021, Australia. zbyszek@cs.adelaide.edu.au.
authors.forename: Zbigniew
authors.initials: Z
authors.lastname: Michalewicz
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D013269:Stochastic Processes
keywords: Particle swarm optimization; constrained optimization.; invariance; local convergence; parameter selection; stability analysis; topology