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Parameter Selection in Particle Swarm Optimisation from Stochastic Stability Analysis

  • Adam Erskine
  • Thomas Joyce
  • J. Michael HerrmannEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9882)

Abstract

Particle swarm optimisation is a metaheuristic algorithm which finds reasonable solutions in a wide range of applied problems if suitable parameters are used. We study the properties of the algorithm in the framework of random dynamical systems (RDS) which, due to the quasi-linear swarm dynamics, yields exact analytical results for the stability properties in the single particle case. The calculated stability region in the parameter space extends beyond the region determined by earlier approximations. This is also evidenced by simulations which indicate that the algorithm performs best in the asymptotic case if parameterised near the margin of instability predicted by the RDS approach.

Keywords

Particle Swarm Optimisation Criticality Random dynamical systems Random matrix products Parameter selection 

Notes

Acknowledgments

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC), grant number EP/K503034/1.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Adam Erskine
    • 1
  • Thomas Joyce
    • 1
  • J. Michael Herrmann
    • 1
    Email author
  1. 1.School of Informatics, Institute for Perception, Action and BehaviourThe University of EdinburghEdinburghScotland, UK

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