Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (18): 8-16.DOI: 10.3778/j.issn.1002-8331.1806-0215

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Survey of cuckoo search algorithm

ZHANG Xiaofeng, WANG Xiuying   

  1. College of Information Science & Technology, Qingdao University of Science & Technology, Qingdao, Shandong 266000, China
  • Online:2018-09-15 Published:2018-10-16



  1. 青岛科技大学 信息科学技术学院,山东 青岛 266000

Abstract: As an efficient swarm-intelligence-based algorithm, Cuckoo Search(CS) algorithm is inspired by the cuckoo breeding behavior in combination with the Lévy flight of some birds and fruit flies. Firstly, the principle of CS algorithm is introduced, and and it is compared with the current mainstream group intelligent algorithm to illustrate the effectiveness and deficiency of CS algorithm. Then the research achievements and application status of CS at home and abroad are introduced in detail, including binary CS, chaotic CS, discrete CS and other versions of CS, and applications in the fields of image processing, data mining, combinatorial optimization and other fields. Finally the further research directions of CS are proposed according to characteristics of CS algorithm and its application research results.

Key words: cuckoo search algorithm, swarm intelligence, optimization algorithm, image processing

摘要: 布谷鸟搜索(Cuckoo Search,CS)算法是一种新型的群体智能优化算法,该算法受布谷鸟的巢寄生育雏行为的启发,并结合鸟类、果蝇等的莱维飞行特征而提出。首先对CS算法的原理进行介绍,并将它与当前主流群智能算法进行对比分析,从而说明CS算法的有效性及不足。然后介绍了算法的国内外研究成果,包括二进制CS、混沌CS、离散CS等多种版本的改进算法,以及CS算法在图像处理、数据挖掘、组合优化等多个领域的应用。最后,结合布谷鸟算法的特点及其应用研究成果,指出CS算法未来的研究方向。

关键词: 布谷鸟搜索算法, 群体智能, 优化算法, 图像处理