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Hypersphere Universe Boundary Method Comparison on HCLPSO and PSO

  • Tomas KadavyEmail author
  • Michal Pluhacek
  • Adam Viktorin
  • Roman Senkerik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10334)

Abstract

In this paper, the hypersphere universe method is applied on Heterogeneous Comprehensive Learning Particle Swarm Optimization (HCLPSO) and a classical representative of swarm intelligence Particle Swarm Optimization (PSO). The goal is to the compare this method to the classical version of these algorithms. The comparisons are made on CEC’17 benchmark set functions. The experiments were carried out according to CEC benchmark rules and statistically evaluated using Friedman rank test.

Keywords

Particle Swarm Optimization PSO Heterogeneous Comprehensive Learning HCLPSO Search space boundaries Roaming particles 

Notes

Acknowledgements

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 Projects no. IGA/CebiaTech/2017/004.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Tomas Kadavy
    • 1
    Email author
  • Michal Pluhacek
    • 1
  • Adam Viktorin
    • 1
  • Roman Senkerik
    • 1
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic

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