Abstract
With the increasing demands in solving larger dimensional problems, it is necessary to have efficient algorithm. Efforts were put towards increasing the efficiency of the algorithms. This paper presents a new approach of particle swarm optimization with cooperative coevolution. The proposed technique [NPSO-CC] is built on the success of an early CCPSO2 that employs an effective variable grouping technique random grouping. The technique of moving away out of the local minima is presented in the paper. Instead of using simple velocity update equation, the new velocity update equation is used from where the contribution of worst particle is subtracted. Experimental results show that our algorithm performs better as compared to other promising techniques on most of the functions.
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Aote, S.S., Raghuwanshi, M.M., Malik, L.G. (2015). A New Particle Swarm Optimizer with Cooperative Coevolution for Large Scale Optimization. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_88
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DOI: https://doi.org/10.1007/978-3-319-11933-5_88
Publisher Name: Springer, Cham
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