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Published in:
2018 | OriginalPaper | Chapter
Particle Swarm Optimization with Single Particle Repulsivity for Multi-modal Optimization
Authors : Michal Pluhacek, Roman Senkerik, Adam Viktorin, Tomas Kadavy
Published in: Artificial Intelligence and Soft Computing
Publisher: Springer International Publishing
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Abstract
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.