Using Self-organized Criticality for Adjusting the Parameters of a Particle Swarm

Carlos M. Fernandes, Juan Julián Merelo, Agostinho C. Rosa

Abstract

The local and global behavior of Self-Organized Criticality (SOC) systems may be an efficient source for controlling the parameters of a Particle Swarm Optimization (PSO) without hand-tuning. This paper proposes a strategy based on the SOC Bak-Sneppen model of co-evolution for adjusting the inertia weight and the acceleration coefficients values of the PSO. In order to increase exploration, the model is also used to perturb the position of the particles. The resulting algorithm is named Bak-Sneppen PSO (BS-PSO). An experimental setup compares the new algorithm with versions of the PSO with varying inertia weight, including a state-of-the-art algorithm with dynamic variation of the weight value and perturbation of the particles’ positions. The parameter values generated by the model are investigated in order to understand the dynamic of the algorithm and explain its performance.

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Paper Citation


in Harvard Style

M. Fernandes C., Merelo J. and C. Rosa A. (2012). Using Self-organized Criticality for Adjusting the Parameters of a Particle Swarm . In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 62-71. DOI: 10.5220/0004158200620071


in Bibtex Style

@conference{ecta12,
author={Carlos M. Fernandes and Juan Julián Merelo and Agostinho C. Rosa},
title={Using Self-organized Criticality for Adjusting the Parameters of a Particle Swarm},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)},
year={2012},
pages={62-71},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004158200620071},
isbn={978-989-8565-33-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: ECTA, (IJCCI 2012)
TI - Using Self-organized Criticality for Adjusting the Parameters of a Particle Swarm
SN - 978-989-8565-33-4
AU - M. Fernandes C.
AU - Merelo J.
AU - C. Rosa A.
PY - 2012
SP - 62
EP - 71
DO - 10.5220/0004158200620071