Open AccessImproved mayfly algorithm based on hybrid mutation
Author(s) -
Zhang Hua,
Liu Zheng,
Gui ShiWeng,
Zou Mei,
Wang PeiYuan
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12568
Subject(s) - mutation , mayfly , population , operator (biology) , algorithm , computer science , genetic algorithm , biology , machine learning , genetics , demography , nymph , repressor , sociology , gene , transcription factor , botany
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.