On the Non Linear Dynamics of the Global Best Particle in Particle Swarm Optimization

The dynamics of Particle swarm optimization has been developed from the collective behavior of the social creatures like fish schooling and gradually has become a powerful global optimization technique. In this paper we do the analysis on a continuous variant of PSO. The non linear dynamics of the global best particle is studied here and the exponential convergence is ensured. The effects of the different control parameters on the convergence of the global best particle are also studied.

[1]  J. F. Martínez,et al.  The generalized PSO: a new door to PSO evolution , 2008 .

[2]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[3]  E. Ozcan,et al.  Particle swarm optimization: surfing the waves , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[4]  Ioan Cristian Trelea,et al.  The particle swarm optimization algorithm: convergence analysis and parameter selection , 2003, Inf. Process. Lett..

[5]  Chilukuri K. Mohan,et al.  Analysis of a simple particle swarm optimization system , 1998 .

[6]  U. Baumgartner,et al.  Particle swarm optimization - mass-spring system analogon , 2002 .

[7]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[8]  James Kennedy,et al.  Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[9]  José Neves,et al.  The fully informed particle swarm: simpler, maybe better , 2004, IEEE Transactions on Evolutionary Computation.