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Improved mayfly algorithm based on hybrid mutation
  • +2
  • Hua Zhang,
  • zheng liu,
  • ShiWeng Gui,
  • Mei Zou,
  • PeiYuan Wang
Hua Zhang
Hubei University of Arts and Science

Corresponding Author:[email protected]

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zheng liu
Hubei University of Arts and Science
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ShiWeng Gui
Hubei University of Arts and Science
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Mei Zou
Hubei University of Arts and Science
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PeiYuan Wang
Hubei University of Arts and Science
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Abstract

To improve the diversity and performance of the Mayfly Algorithm (MA), this letter adopts the mutation strategies in the process of MA. The opposition-based learning (OBL) and Cauchy mutation strategies are used to mutate the global optimal solution, and the artificial mutation operator is used in the offspring population. The hybrid mutation strategies are used in a cascaded structure. The performance of the proposed algorithms is demonstrated in simulations comparatively.
23 May 2022Submitted to Electronics Letters
23 May 2022Assigned to Editor
23 May 2022Submission Checks Completed
10 Jun 2022Reviewer(s) Assigned
17 Jun 2022Review(s) Completed, Editorial Evaluation Pending
19 Jun 2022Editorial Decision: Accept
03 Jul 2022Published in Electronics Letters. 10.1049/ell2.12568