Improved Exploration and Exploitation in Particle Swarm Optimization

  • Dania Tamayo-Vera
  • Stephen Chen
  • Antonio Bolufé-Röhler
  • James Montgomery
  • Tim Hendtlass
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10868)


Exploration and exploitation are analyzed in Particle Swarm Optimization (PSO) through a set of experiments that make new measurements of these key features. Compared to analyses on diversity and particle trajectories, which focus on particle motions and their potential to achieve exploration and exploitation, our analysis also focuses on the pbest positions that reflect the actual levels of exploration and exploitation that have been achieved by PSO. A key contribution of this paper is a clear criterion for when restarting particles can be expected to be a useful strategy in PSO.


Exploration Exploitation Particle Swarm Optimization Multi-modal search spaces 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Dania Tamayo-Vera
    • 1
  • Stephen Chen
    • 2
  • Antonio Bolufé-Röhler
    • 1
  • James Montgomery
    • 3
  • Tim Hendtlass
    • 4
  1. 1.School of Mathematics and Computer ScienceUniversity of HavanaHavanaCuba
  2. 2.School of Information TechnologyYork UniversityTorontoCanada
  3. 3.School of Technology, Environments and DesignUniversity of TasmaniaHobartAustralia
  4. 4.Department of Computer Science and Software EngineeringSwinburne University of TechnologyMelbourneAustralia

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