Abstract
In this paper, the novel concept of particle performance evaluation within the particle swarm optimization algorithm (PSO) is introduced. In this method the contribution of each particle to the process of obtaining the global best solution is investigated periodically. For the particle with no contribution to the global best solution over a given number of iterations the velocity calculation is changed; in the case of this presented research, in order to improve its performance towards the global trend.
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Pluhacek, M., Senkerik, R., Zelinka, I. (2014). Preliminary Study on the Particle Swarm Optimization with the Particle Performance Evaluation. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8467. Springer, Cham. https://doi.org/10.1007/978-3-319-07173-2_34
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DOI: https://doi.org/10.1007/978-3-319-07173-2_34
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07172-5
Online ISBN: 978-3-319-07173-2
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