A many-objective evolutionary algorithm based on reference vector guided selection and two diversity and convergence enhancement strategies

Achieving the balance between convergence and diversity is a key and challenging issue in many-objective optimization. Reference vector guided selection is an exemplary method for decomposition-based many-objective evolutionary algorithms (MaOEAs). However, there are some problems with it such as in...

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Veröffentlicht in:	Applied soft computing Jg. 154; S. 111369
Hauptverfasser:	Yang, Lei, Zhang, Yuanye, Cao, Jiale, Li, Kangshun, Wang, Dongya
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.03.2024
Schlagworte:	Convergence and diversity enhancement Many-objective optimization Reference vector Reference vector Convergence and diversity enhancement Many-objective optimization
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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