Abstract
In this paper, a new version of Particle Swarm Optimization (PSO) Algorithm has been proposed where the velocity update equation of PSO has been modified. A new term is added withthe original velocity update equation by calculating difference between the global best of swarm and local best of particles. The proposed method is applied on eight well known benchmark problems and experimental results are compared with the standard PSO (SPSO). From the experimental results, it has been observed that the newly proposed PSO algorithm outperforms the SPSO in terms of convergence, speed and quality.
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Jana, N.D., Si, T., Sil, J. (2013). Fast Convergence in Function Optimization Using Modified Velocity Updating in PSO Algorithm. In: Satapathy, S., Udgata, S., Biswal, B. (eds) Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA). Advances in Intelligent Systems and Computing, vol 199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35314-7_58
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DOI: https://doi.org/10.1007/978-3-642-35314-7_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35313-0
Online ISBN: 978-3-642-35314-7
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