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Population Control in Evolutionary Algorithms: Review and Comparison

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Bio-inspired Computing: Theories and Applications (BIC-TA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 791))

Abstract

Population size in evolutionary algorithms (EAs) is critical for their performance. In this paper, we first give a comprehensive review of existing population control methods. Then, a few representative methods are selected and empirically compared on a range of well-known benchmark functions to show their pros and cons.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Grant No. 61573316).

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Authors and Affiliations

  1. College of Computer Science, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, People’s Republic of China

    Yuyang Guan & Ling Yang

  2. Department of Computer Science, Hangzhou Normal University, Hangzhou, 311121, Zhejiang, People’s Republic of China

    Weiguo Sheng

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  1. Yuyang Guan
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  2. Ling Yang
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  3. Weiguo Sheng
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Correspondence to Weiguo Sheng .

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Editors and Affiliations

  1. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Cheng He

  2. Automation College, Harbin Engineering University, Harbin, China

    Hongwei Mo

  3. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Automation College, Harbin Engineering University, Harbin, China

    Yuxin Zhao

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Guan, Y., Yang, L., Sheng, W. (2017). Population Control in Evolutionary Algorithms: Review and Comparison. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_13

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