Cuckoo search with varied scaling factor

doi:10.1007/s11704-015-4178-y

Front. Comput. Sci.

2015, Vol. 9

Issue (4) : 623-635 https://doi.org/10.1007/s11704-015-4178-y

RESEARCH ARTICLE

Cuckoo search with varied scaling factor

Lijin WANG^1,²,Yilong YIN^1,^3,^*(

),Yiwen ZHONG²

1. School of Computer Science and Technology, Shandong University, Jinan 250101, China
2. College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan 250014, China

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Abstract

Cuckoo search (CS), inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses Lévy flights random walk (LFRW) and biased/selective random walk (BSRW) to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scaling factor (VSF) strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS variants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions introduced in CEC 2013. Experimental results demonstrate the effectiveness of the VSF strategy.

Keywords cuckoo search algorithm uniform distribution random sampling scaling factor function optimization problems

Corresponding Author(s): Yilong YIN

Just Accepted Date: 22 April 2015 Issue Date: 07 September 2015

Cite this article:

Lijin WANG,Yilong YIN,Yiwen ZHONG. Cuckoo search with varied scaling factor[J]. Front. Comput. Sci., 2015, 9(4): 623-635.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-015-4178-y
https://academic.hep.com.cn/fcs/EN/Y2015/V9/I4/623

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