An enhanced reference vectors-based multi-objective evolutionary algorithm with neighborhood-based adaptive adjustment

The decomposition-based evolutionary algorithms have shown great potential in multi-objective optimization and many-objective optimization. However, their performance strongly depends on the Pareto front shapes. This may result from the fixed reference vectors, which will waste computing resources w...

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Vydané v:	Neural computing & applications Ročník 32; číslo 15; s. 11767 - 11789
Hlavní autori:	Fan, Rui, Wei, Lixin, Sun, Hao, Hu, Ziyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Springer London 01.08.2020 Springer Nature B.V
Predmet:	Adaptive algorithms Artificial Intelligence Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Computer simulation Convergence Data Mining and Knowledge Discovery Evolutionary algorithms Genetic algorithms Image Processing and Computer Vision Multiple criterion Multiple objective analysis Neighborhoods Original Article Pareto optimization Probability and Statistics in Computer Science Shape optimization Solution space Multi-objective optimization Many-objective optimization Reference vector Adaptive adjustment Evolutionary computation
ISSN:	0941-0643, 1433-3058
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