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A new mutation operator for differential evolution algorithm

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Abstract

The widely employed mutation operator \(DE/current-to-pbest/1\) in the differential evolution algorithm (DE) is further developed to a new version \(DE/current-to-pbest/1-X\) in this paper. To test its performance, it has been embedded in the novel successful history-based adaptive DE (L-SHADE) and compared with other recently proposed mutation operators. In \(DE/current-to-pbest/1-X\), the updated parameter memories in each generation are not adopted when the initial value can still maintain an acceptable successful rate of finding better offspring. Also, the generated worse offsprings with acceptable fitness values are partially archived to generate differential vectors. The experimental results show that \(DE/current-to-pbest/1-X\) has a comparable performance than \(DE/current-to-pbest/1\), \(DE/current-to-ord\_pbest/1\) and \(DE/current-to-ord\_best/1\).

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Notes

  1. F2 has been deleted from the CEC2017 test suite

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Acknowledgements

This work is supported by “the Fundamental Research Funds for the Central Universities” (grant number JAI210003)

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Authors and Affiliations

  1. Artificial Intelligence Research Institute, China University of Mining and Technology, Xuzhou, 221116, China

    Mingcheng Zuo

  2. School of Computer Science, China University of Geosciences (Wuhan), No. 388 LuMo Road, Hongshan District, Wuhan, China

    Guangming Dai & Lei Peng

  3. Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, China

    Guangming Dai & Lei Peng

  4. Key Laboratory of Geological Survey and Evaluation of Ministry of Education, Wuhan, China

    Lei Peng

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  1. Mingcheng Zuo
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  2. Guangming Dai
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  3. Lei Peng
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Contributions

Mingcheng Zuo: Conducting the code, the experiments and the writing. Guangming Dai and Lei Peng: Check the code and the experiments.

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Correspondence to Mingcheng Zuo.

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Zuo, M., Dai, G. & Peng, L. A new mutation operator for differential evolution algorithm. Soft Comput 25, 13595–13615 (2021). https://doi.org/10.1007/s00500-021-06077-6

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