A dynamic multi-objective optimization algorithm based on probability-driven prediction and correlation-guided individual transfer

The primary challenge in addressing dynamic multi-objective optimization problems (DMOPs) is the rapid tracking of optimal solutions. Although methods based on transfer learning have shown remarkable performance in tackling DMOPs, most existing methods overlook the potential relationships between in...

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Vydané v:	The Journal of supercomputing Ročník 81; číslo 1; s. 348
Hlavní autori:	Ge, Fangzhen, Zhao, Xuan, Chen, Debao, Shen, Longfeng, Liu, Huaiyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer Nature B.V 01.01.2025
Predmet:	Algorithms Annotations Correlation Genetic algorithms Kalman filters Multiple objective analysis Optimization Pareto optimum Trends
ISSN:	0920-8542, 1573-0484
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