An online-learning-based evolutionary many-objective algorithm

When optimizing many-objective problems (MaOP), the same strategy might behave differently when facing problems with different features. Therefore, obtaining problem features helps to obtain high-quality solutions. However, in practice, the problem features are unknown during the optimization proces...

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Veröffentlicht in:	Information sciences Jg. 509; S. 1 - 21
Hauptverfasser:	Zhao, Haitong, Zhang, Changsheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.01.2020
Schlagworte:	Decomposition strategy Evolutionary algorithm Many-objective optimization Online-learning Online-learning Many-objective optimization Evolutionary algorithm Decomposition strategy
ISSN:	0020-0255, 1872-6291
Online-Zugang:	Volltext
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