Dynamic multi-objective optimization algorithm based on incremental Gaussian mixture model

In recent years, prediction-based algorithms have made significant progress in solving dynamic multi-objective optimization problems (DMOPs). However, most existing methods only consider information from several consecutive environments and ignore past search experiences. To address the issue, this...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 98; S. 102067
Hauptverfasser:	Xia, Xuewen, Zeng, Yi, Xu, Xing, Zhang, Yinglong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.10.2025
Schlagworte:	Data augmentation Dynamic multi-objective optimization algorithm Incremental Gaussian mixture model (IGMM) Polynomial mutation Polynomial mutation Data augmentation Incremental Gaussian mixture model (IGMM) Dynamic multi-objective optimization algorithm
ISSN:	2210-6502
Online-Zugang:	Volltext
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