Differential Evolution With Ranking-Based Mutation Operators

By Wenyin Gong, Zhihua Cai. IEEE Transactions on Cybernetics, 2013

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A Survey on Evolutionary Constrained Multiobjective Optimization (2023, background): “To be speciﬁc, the preference for the objectives is gradually reduced from 1 to 0 according to the designed cosine function curve [47], [48].”
Recent advances in differential evolution - An updated survey (2016, background): “Gong and Cai [74] suggest that a mutation can be more fruitful if the base vector and one of the terminal vectors of the difference vector can be selected based on their fitness, while the third is selected at random.”
Parameter extraction of solar cell models using repaired adaptive differential evolution (2013, methodology): “Therefore, in order to reduce the computational efforts and make the parameter extractio n pr cess of solar cell models faster, in this work, the ranking-based vector selection technique [37] is used in th e above mutation operator.”
Differential evolution with multi-population based ensemble of mutation strategies (2016, background): “In [18], ranking-based mutation operators were designed and incorporated into classical mutation strategies, which results in significant performance improvement.”