Multi-chaotic Approach for Particle Acceleration in PSO

  • Michal PluhacekEmail author
  • Roman Senkerik
  • Adam Viktorin
  • Ivan Zelinka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9668)


This paper deals with novel approach for hybridization of two scientific techniques: the evolutionary computational techniques and deterministic chaos. The Particle Swarm Optimization algorithm is enhanced with two pseudo-random number generators based on chaotic systems. The chaotic pseudo-random number generators (CPRNGs) are used to guide the particles movement through multiplying the accelerating constants. Different CPRNGs are used simultaneously in order to improve the performance of the algorithm. The IEEE CEC’13 benchmark suite is used to test the performance of the proposed method.


Particle swarm optimization PSO Chaos Acceleration constant 



This work was supported by Grant Agency of the Czech Republic – GACR P103/15/06700S, further by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014). Also by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Project no. IGA/Ceb-iaTech/2016/007.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Michal Pluhacek
    • 1
    Email author
  • Roman Senkerik
    • 1
  • Adam Viktorin
    • 1
  • Ivan Zelinka
    • 2
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic
  2. 2.Faculty of Electrical Engineering and Computer ScienceTechnical University of OstravaOstrava-PorubaCzech Republic

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