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SCJADE : Yet Another State‐of‐the‐Art Differential Evolution Algorithm
Author(s) -
Xu Zhe,
Gao Shangce,
Yang Haichuan,
Lei Zhenyu
Publication year - 2021
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.23340
Subject(s) - roulette , differential evolution , convergence (economics) , fitness proportionate selection , algorithm , computer science , state (computer science) , selection (genetic algorithm) , evolutionary algorithm , chaotic , differential (mechanical device) , mathematical optimization , mathematics , artificial intelligence , engineering , genetic algorithm , machine learning , geometry , aerospace engineering , fitness function , economics , economic growth
Differential evolution algorithms have become one of the most competitive evolutionary algorithms, among which a chaotic differential evolution (CJADE) is a recently proposed state‐of‐the‐art variant. But CJADE still suffers from the premature convergence problem. This paper further improves CJADE by innovatively incorporating a success‐intensity‐based roulette wheel selection method into it. The resultant algorithm called SCJADE shows its superiority over its peer in terms of solution quality and convergence speed on IEEE CEC2017 optimization test suit. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.