An analysis of Bare Bones Particle Swarm

The bare bones particle swarm (BBPS) is evolved from the canonical particle swarm optimizer (PSO). The velocity term of the canonical PSO is removed in BBPS and replaced by Gaussian sampling strategy. There is no parameter tuning and it is much easier to implement. In the paper, it is proven that the BBPS can be mathematically deduced from the canonical PSO and a more general formula of BBPS is also presented. The results presented in the paper represent initial results of an ongoing research project effort.

[1]  Andries Petrus Engelbrecht,et al.  Differential Evolution Based Particle Swarm Optimization , 2007, 2007 IEEE Swarm Intelligence Symposium.

[2]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[3]  Kevin D. Seppi,et al.  Exposing origin-seeking bias in PSO , 2005, GECCO '05.

[4]  Mahamed G. H. Omran,et al.  Barebones particle swarm methods for unsupervised image classification , 2007, 2007 IEEE Congress on Evolutionary Computation.

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

[6]  James Kennedy,et al.  Particle swarm optimization , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[7]  Visakan Kadirkamanathan,et al.  Stability analysis of the particle dynamics in particle swarm optimizer , 2006, IEEE Transactions on Evolutionary Computation.

[8]  Andries Petrus Engelbrecht,et al.  Barebones Particle Swarm for Integer Programming Problems , 2007, 2007 IEEE Swarm Intelligence Symposium.

[9]  James Kennedy,et al.  Bare bones particle swarms , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[10]  Riccardo Poli,et al.  Markov chain models of bare-bones particle swarm optimizers , 2007, GECCO '07.

[11]  M. Clerc Stagnation Analysis in Particle Swarm Optimisation or What Happens When Nothing Happens , 2006 .

[12]  Jie Chen,et al.  Common model analysis and improvement of particle swarm optimizer , 2007 .