Summary

Proceedings of the 2012 International Symposium on Nonlinear Theory and its Applications

2012

Session Number:A3L-A

Session:

Number:146

Parameter Setting Procedure by using Golden Angle for Generation of Diversity

Takuya Shindo,  Kenya jin'no,  

pp.146-149

Publication Date:

Online ISSN:2188-5079

DOI:10.15248/proc.1.146

PDF download (1.1MB)

Summary:
In our previous studies, we confirmed that the deterministic PSO which was removed the stochastic factors from the conventional PSO to analyze its dynamics, has bad search performance comparing with the conventional PSO. The cause is that the parameters in the deterministic PSO is time invariant, namely, each particle doesn't have diversity. Based on a golden angle property, we propose a parameter setting procedure for the deterministic PSO to generate diversity. In this article, we confirm the optimal solution search performance of proposed parameter setting procedure using plural benchmark functions.

References:

[1] J. Kennedy and R. Eberhart, “Particle Swarm Optimization”, in Proc. IEEE Int. Conf. Neural Networks, pp. 1942-1948, 1995.

[2] J. Kennedy, “The particle swarm: Social adaptation of knowledge,” in Proc. IEEE Int. Conf. Evolutionary Computation, pp. 303-308, 1997.

[3] Y. Shi and R. Eberhart, “Empirical study of particle swarm optimization,” in Proc. ICEC 1999, pp. 1945-1950, 1999.

[4] M. Clerc and J. Kennedy, “The particle swarm - explosion, stability, and convergence in a multidimensional complex space,” IEEE Trans. Evol. Comput., vol. 6, no. 1, pp. 58-73, 2002.

[5] F. van den Bergh and A. P. Engelbrecht, “A cooperative approach to particle swarm optimization,” IEEE Trans. Evol. Comput., vol. 8, no. 3, pp. 225-239, 2004.

[6] V. Kadirkamanathan, K. Selvarajah, and P. J. Fleming, “Stability analysis of the particle dynamics in particle swarm optimizer,” IEEE Trans. Evol. Comput., vol. 10, no. 3, pp. 245-255, 2006.

[7] E. F. Campana, G. Fasano, D. Peri and A. Pinto “Particle swarm optimization: efficient globally convergent modifications,” in Proc. III European Conference on Computational Mechanics Solids, Structures and Coupled Problems in Engineering, 2006.

[8] T. Kanda, T. Kurihara, T. Shindo, and K. Jin'no, “A-2-21 investigation of circuit implementation of particle swarm optimizer,” Proceedings of the Society Conference of IEICE, vol. 2011, p. 58, 2011.