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A novel differential evolution algorithm based on periodic intervention and systematic regulation mechanisms

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Abstract

Differential evolution (DE) has attracted widespread attention due to its outstanding optimization performance and ease of operation, but it cannot avoid the dilemmas of premature convergence or stagnation when faced with complex optimization problems. To reduce the probability of such difficulties for DE, we sort out the factors that influence the balance between global exploration and local exploitation in the DE algorithm, and we design a novel DE variant (abbreviated as PISRDE) by integrating the corresponding influence factors through a periodic intervention mechanism and a systematic regulation mechanism. The periodic intervention mechanism divides the optimization operations of PISRDE into routine operation and intervention operation, and it balances global exploration and local exploitation at the macro level by executing the two operations alternately. The systematic regulation mechanism treats the involved optimization strategies and parameter settings as an organic system for targeted design, to balance global exploration and local exploitation at the meso or micro level. To evaluate and verify the optimization performance of PISRDE, we employ seven DE variants with excellent optimization performance to conduct comparison experiments on the IEEE CEC 2014 and IEEE CEC 2017 benchmarks. The comparison results indicate that PISRDE outperforms all competitors overall, and its relative advantage is even more significant when dealing with high-dimensional and complex optimization problems.

Graphical abstract

Schematic design philosophy of PISRDE

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Data Availability and Access

All authors have reviewed and approved the final manuscript submitted and the data utilized in this paper. The test benchmarks and comparison algorithms employed in this paper are detailed in the corresponding references, and the experimental data for proposed algorithm are shown in the Supplementary Material

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant No.62176075 and No.71701187), National Key R&D Program of China (Grant No.2022YFB3304000), and Shandong Provincial Natural Science Foundation (Grant No.ZR2021MF063).

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Authors and Affiliations

  1. School of Information Science and Engineering, Harbin Institute of Technology, 264209, Weihai, China

    Guanyu Yuan, Libao Deng & Chunlei Li

  2. College of Economics and Management, Zhejiang Normal University, 321004, Jinhua, China

    Gaoji Sun

  3. School of Electronics and Information Engineering, Harbin Institute of Technology, 150001, Harbin, China

    Chunlei Li

  4. School of Management, Hebei University, 071002, Baoding, China

    Guoqing Yang

Authors
  1. Guanyu Yuan
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Contributions

Conceptualization: Gaoji Sun, Libao Deng; Methodology: Gaoji Sun; Formal analysis: Gaoji Sun, Chunlei Li; Software: Gaoji Sun, Guoqing Yang; Data curation and visualization: Guanyu Yuan, Chunlei Li; Writing - original draft: Guanyu Yuan, Gaoji Sun; Writing - review and editing: Guanyu Yuan, Gaoji Sun, Libao Deng, Chunlei Li, Guoqing Yang; Funding acquisition: Gaoji Sun, Libao Deng, Guoqing Yang; Supervision: Gaoji Sun, Libao Deng.

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Correspondence to Gaoji Sun or Libao Deng.

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Yuan, G., Sun, G., Deng, L. et al. A novel differential evolution algorithm based on periodic intervention and systematic regulation mechanisms. Appl Intell 54, 11779–11803 (2024). https://doi.org/10.1007/s10489-024-05781-8

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