A self-adaptive dynamic multi-objective optimization algorithm based on transfer learning and elitism-based mutation

Dynamic multi-objective optimization problems (DMOPs) involve several conflicting objectives, and these objective functions change over time. Therefore, addressing DMOPs necessitates an effective response to environmental changes. However, most existing algorithms only deal with DMOPs with one parti...

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Vydáno v:	Neurocomputing (Amsterdam) Ročník 559; s. 126761
Hlavní autoři:	Zhang, Xi, Jin, Yaochu, Qian, Feng
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 28.11.2023
Témata:	Diversity introduction Dynamic multi-objective optimization Self-adaptive change response Transfer learning Self-adaptive change response Diversity introduction Dynamic multi-objective optimization Transfer learning
ISSN:	0925-2312, 1872-8286
On-line přístup:	Získat plný text
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