A dynamic multi-objective evolutionary algorithm based on Mahalanobis distance and intra-cluster individual correlation rectification

Responding quickly and accurately to environmental changes is a challenge in addressing dynamic multi-objective optimization problems (DMOPs). Although many dynamic multi-objective evolutionary algorithms (DMOEAs) have demonstrated impressive performance, there is still room for improvement in accur...

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Veröffentlicht in:	Information sciences Jg. 678; S. 120922
Hauptverfasser:	Ge, Fangzhen, Hou, Xing, Chen, Debao, Shen, Longfeng, Liu, Huaiyu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.09.2024
Schlagworte:	Correlation analysis Dynamic multi-objective optimization Evolutionary algorithms Mahalanobis distance Prediction Time series Evolutionary algorithms Dynamic multi-objective optimization Correlation analysis Mahalanobis distance Prediction Time series
ISSN:	0020-0255, 1872-6291
Online-Zugang:	Volltext
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