| Citation: | ZHANG Kewei, ZHAO Xiaolin, HE Li, et al. A chicken swarm optimization algorithm based on improved X-best guided individual and dynamic hierarchy update mechanism[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(12): 2579-2593. doi: 10.13700/j.bh.1001-5965.2020.0322(in Chinese)
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In the improvement process of swarm intelligence algorithms, elite individuals are often used to accelerate the convergence, but excessive dependence on them will lead to the decline of population diversity and global convergence. In this regard, a chicken swarm optimization algorithm based on improved X-best guided individual and dynamic hierarchy update mechanism is proposed in this paper. Firstly, in the individual update stage, elite individuals are introduced into the search equation to accelerate the convergence, while the ordinary individuals are also introduced into the search equation to balance the influence of the elite individuals. Therefore, the information of elite and ordinary individuals can be fully used, and the population diversity and global convergence are improved. Secondly, by dynamically optimizing the hierarchy update parameter, the promotion effect of the population hierarchy update mechanism on the convergence is strengthened. Finally, through complexity and convergence analysis, the simplicity and global convergence of IDCSO are proved. The simulation results show that IDCSO has obvious advantages over other comparative algorithms in terms of optimization accuracy, optimization success rate and convergence speed.
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