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International Joint Conference on Computational Intelligence

IJCCI 2015: Computational Intelligence pp 175–194Cite as

Particle Convergence Time in the Deterministic Model of PSO

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 669))

Abstract

A property of particles in Particle Swarm Optimization (PSO), namely, particle convergence time (pct) is a subject of theoretical and experimental analysis. For the model of PSO with inertia weight a new measure for evaluation of pct is proposed. The measure evaluates number of steps necessary for a particle to obtain a stable state defined with any precision. For this measure an upper bound formula of pct is derived and its properties are studied. Four main types of particle behaviour characteristics are selected and discussed. In the experimental part of the research effectiveness of swarms with different characteristics of their members are verified. A new type of swarm control improving efficiency of a swarm in escaping traps of local optima is proposed and experimentally verified.

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Acknowledgements

Authors would like to thank Krzysztof Jura from Cardinal Stefan Wyszyński University in Warsaw, Poland, for his assistance in computer simulations.

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Authors and Affiliations

  1. Faculty of Mathematics and Natural Sciences, School of Exact Sciences, Cardinal Stefan Wyszyński University in Warsaw, Wóycickiego 1/3, 01-938, Warsaw, Poland

    Krzysztof Trojanowski & Tomasz Kulpa

Authors
  1. Krzysztof Trojanowski
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  2. Tomasz Kulpa
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Corresponding author

Correspondence to Tomasz Kulpa .

Editor information

Editors and Affiliations

  1. Computer Architecture and Computer Technology, Universidad de Granada, Granada, Spain

    Juan Julián Merelo

  2. aSEEB-ISR-IST, Technical University of Lisbon (IST), Lisbon, Portugal

    Agostinho Rosa

  3. Facultad de Informática, University of Murcia, Murcia, Spain

    José M. Cadenas

  4. Departamento de Engenharia Informatica, University of Coimbra, Coimbra, Portugal

    António Dourado Correia

  5. Images, Signals and Intelligence Systems Laboratory, University PARIS-EST Creteil (UPEC), Créteil, France

    Kurosh Madani

  6. Campus de Gambelas, Universidade do Algarve, Faro, Portugal

    António Ruano

  7. Escola Superior de Tecnologia de Setúbal, Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

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Trojanowski, K., Kulpa, T. (2017). Particle Convergence Time in the Deterministic Model of PSO. In: Merelo, J.J., et al. Computational Intelligence. IJCCI 2015. Studies in Computational Intelligence, vol 669. Springer, Cham. https://doi.org/10.1007/978-3-319-48506-5_10

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  • DOI: https://doi.org/10.1007/978-3-319-48506-5_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48504-1

  • Online ISBN: 978-3-319-48506-5

  • eBook Packages: EngineeringEngineering (R0)

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