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A new multi-stage perturbed differential evolution with multi-parameter adaption and directional difference

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Abstract

A new multi-stage perturbed differential evolution (MPDE) is proposed in this paper. A new mutation strategy “multi-stage perturbation” is implemented with directivity difference information strategy and multiple parameters adaption. The DE/current-to-pbest is introduced to increase the population diversity while remaining its elitist learning behavior in this architecture. The multi-stage perturbation-based mutation operation utilizes the Normal random distribution with adjustable variance to perturb the chosen solutions. Multiple parameters are adaptively adjusted to appropriate values to match the current search status of algorithm. It is thus helpful to enhance the performance and the robustness of algorithm. Simulation results show that the newly proposed MPDE is better than, or at least comparable to CLPSO, SPSO2011, NGHS, jDE, CoDE, SaDE and JADE algorithms in terms of optimization performance based on CEC2015 benchmark function.

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Acknowledgements

This research is supported by National Natural Science Foundation of China (61375066, 71772060).

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Authors and Affiliations

  1. Automation School, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Guangzhi Xu & Rui Li

  2. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Guangzhi Xu, Rui Li & Xinchao Zhao

  3. School of Statistics, University of International, Business and Economics, Beijing, 10029, China

    Junling Hao

  4. School of Electronics Engineering and Computer Science, Peking University, Beijing, 100871, China

    Ying Tan

Authors
  1. Guangzhi Xu
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  2. Rui Li
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  3. Junling Hao
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  4. Xinchao Zhao
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  5. Ying Tan
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Corresponding author

Correspondence to Xinchao Zhao.

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Xu, G., Li, R., Hao, J. et al. A new multi-stage perturbed differential evolution with multi-parameter adaption and directional difference. Nat Comput 19, 683–698 (2020). https://doi.org/10.1007/s11047-018-9692-z

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  • DOI: https://doi.org/10.1007/s11047-018-9692-z

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