Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity

doi:10.1364/ao.57.002747

CIOMP OpenIR

	Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity
	Qi, X.; Ju, G. H.; Xu, S. Y.
	2018
发表期刊	Applied Optics
ISSN	1559-128X
卷号	57 期号:11 页码:2747-2757
摘要	The phase diversity (PD) technique needs optimization algorithms to minimize the error metric and find the global minimum. Particle swarm optimization (PSO) is very suitable for PD due to its simple structure, fast convergence, and global searching ability. However, the traditional PSO algorithm for PD still suffers from the stagnation problem (premature convergence), which can result in a wrong solution. In this paper, the stagnation problem of the traditional PSO algorithm for PD is illustrated first. Then, an explicit strategy is proposed to solve this problem, based on an in-depth understanding of the inherent optimization mechanism of the PSO algorithm. Specifically, a criterion is proposed to detect premature convergence; then a redistributing mechanism is proposed to prevent premature convergence. To improve the efficiency of this redistributing mechanism, randomized Halton sequences are further introduced to ensure the uniform distribution and randomness of the redistributed particles in the search space. Simulation results show that this strategy can effectively solve the stagnation problem of the PSO algorithm for PD, especially for large-scale and high-dimension wavefront sensing and noisy conditions. This work is further verified by an experiment. This work can improve the robustness and performance of PD wavefront sensing. (C) 2018 Optical Society of America
关键词	microscopy ao-storm adaptive optics retrieval algorithms genetic algorithm sequences Optics
DOI	10.1364/ao.57.002747
收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/60972
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Qi, X.,Ju, G. H.,Xu, S. Y.. Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity[J]. Applied Optics,2018,57(11):2747-2757.
APA	Qi, X.,Ju, G. H.,&Xu, S. Y..(2018).Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity.Applied Optics,57(11),2747-2757.
MLA	Qi, X.,et al."Efficient solution to the stagnation problem of the particle swarm optimization algorithm for phase diversity".Applied Optics 57.11(2018):2747-2757.

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