An Improved Particle Swarm Optimization Based on Biological Chemotaxis

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Standard particle swarm algorithm for function optimization prone to local optimal and premature convergence, and thus the biological chemotaxis principle introduction to particle swarm optimization algorithm, this paper proposed an improved algorithm to maintain the diversity of the populationand the choice of key parameters. Simulation results show that, compared with the traditional particle swarm optimization algorithm, an improved particle swarm algorithm for dealing with complex multimodal function optimization problem can be significantly improved algorithm for global optimization.

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Edited by:

Z.S. Liu, L.P. Xu, X.D. Liang, Z.H. Wang and H.M. Zhang

Pages:

737-740

Citation:

H. Xia, "An Improved Particle Swarm Optimization Based on Biological Chemotaxis", Advanced Materials Research, Vol. 1015, pp. 737-740, 2014

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August 2014

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