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Cuckoo search with varied scaling factor

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An Erratum to this article was published on 18 April 2016

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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.

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Change history

  • 18 April 2016

    In this article, the bracket in the denominator of Eq. (6) is incorrect.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Jinan, 250101, China

    Lijin Wang & Yilong Yin

  2. College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China

    Lijin Wang & Yiwen Zhong

  3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, 250014, China

    Yilong Yin

Authors
  1. Lijin Wang
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  2. Yilong Yin
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  3. Yiwen Zhong
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Corresponding author

Correspondence to Yilong Yin.

Additional information

Lijin Wang received his BS in 2000 and his MS in 2005 from Fujian Agriculture and Forestry University, China, and his PhD in 2008 from Beijing Forestry University, China. He is currently a post-doctoral fellow with the School of Computer Science and Technology, Shandong University, China. He is also an associate professor with the College of Computer and Information Science, Fujian Agriculture and Forestry University. His research interests include evolutionary algorithms and intelligent information processing.

Yilong Yin received his PhD in 2000 from Jilin University, China. From 2000 to 2002, he worked as a postdoctoral fellow in the Department of Electronics Science and Engineering, Nanjing University, China. He is currently the Director of MLA Group and a Professor of the School of Computer Science and Technology, Shandong University, China. His research interests include machine learning, data mining, and computational medicine.

Yiwen Zhong received his MS in 2002 and his PhD in 2005 from Zhejiang University, China. He is currently a professor with the College of Computer and Information Science, Fujian Agriculture and Forestry University, China. From 2007 to 2008, and from 2011 to 2012, he was a visiting scholar in Indiana University, USA. His research interests include computational intelligence, data visualization, and bioinformatics.

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Wang, L., Yin, Y. & Zhong, Y. Cuckoo search with varied scaling factor. Front. Comput. Sci. 9, 623–635 (2015). https://doi.org/10.1007/s11704-015-4178-y

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  • DOI: https://doi.org/10.1007/s11704-015-4178-y

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