Achievement scalarizing function sorting for strength Pareto evolutionary algorithm in many-objective optimization

Multi-objective evolutionary algorithms (MOEAs) have proven their effectiveness in solving two or three objective problems. However, recent research shows that Pareto-based MOEAs encounter selection difficulties facing many similar non-dominated solutions in dealing with many-objective problems. In...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 33; no. 11; pp. 6369 - 6388
Main Authors:	Li, Xin, Li, Xiaoli, Wang, Kang, Yang, Shengxiang, Li, Yang
Format:	Journal Article
Language:	English
Published:	London Springer London 01.06.2021 Springer Nature B.V
Subjects:	Artificial Intelligence Clustering Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Convergence Data Mining and Knowledge Discovery Evolutionary algorithms Genetic algorithms Image Processing and Computer Vision Multiple objective analysis Optimization Original Article Probability and Statistics in Computer Science Sorting algorithms Strategy Achievement scalarizing function Many-objective optimization Evolutionary algorithm Diversity Convergence
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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