Particle Swarm Optimization with Single Particle Repulsivity for Multi-modal Optimization

  • Michal PluhacekEmail author
  • Roman Senkerik
  • Adam Viktorin
  • Tomas Kadavy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10841)


This work presents a simple but effective modification of the velocity updating formula in the Particle Swarm Optimization algorithm to improve the performance of the algorithm on multi-modal problems. The well-known issue of premature swarm convergence is addressed by a repulsive mechanism implemented on a single-particle level where each particle in the population is partially repulsed from a different particle. This mechanism manages to prolong the exploration phase and helps to avoid many local optima. The method is tested on well-known and typically used benchmark functions, and the results are further tested for statistical significance.


Particle Swarm Optimization PSO Convergence Repulsivity 


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic

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