Abstract
We consider particle swarm optimization algorithm with a constriction coefficient and investigate particle dynamics without stagnation assumptions. We propose differential models of a particle following the swarm leader, while global best and personal best position are changing. We introduce three qualitative kinds of particles – a leader, a lazy follower and a sedulous follower with equations allowing quantitative investigation of parameter influence. This analysis constitutes an attempt to understand PSO dynamics and the choice of swarm parameters and inspires parameters adaptation.
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Kabziński, J. (2011). Following the Leader – Particle Dynamics in Constricted PSO. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23938-0_47
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DOI: https://doi.org/10.1007/978-3-642-23938-0_47
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