An efficient mixture sampling model for gaussian estimation of distribution algorithm

Estimation of distribution algorithm (EDA) is a stochastic optimization algorithm based on probability distribution model and has been widely applied in global optimization. However, the random sampling of Gaussian EDA (GEDA) usually suffers from the poor diversity and the premature convergence, whi...

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Veröffentlicht in:	Information sciences Jg. 608; S. 1157 - 1182
Hauptverfasser:	Dang, Qianlong, Gao, Weifeng, Gong, Maoguo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.08.2022
Schlagworte:	Efficient mixture sampling model Evolutionary algorithm Gaussian estimation of distribution algorithm Premature convergence Efficient mixture sampling model Premature convergence Evolutionary algorithm Gaussian estimation of distribution algorithm
ISSN:	0020-0255, 1872-6291
Online-Zugang:	Volltext
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