A Survey on Learnable Evolutionary Algorithms for Scalable Multiobjective Optimization

Recent decades have witnessed great advancements in multiobjective evolutionary algorithms (MOEAs) for multiobjective optimization problems (MOPs). However, these progressively improved MOEAs have not necessarily been equipped with scalable and learnable problem-solving strategies for new and grand...

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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Liu, Songbai, Lin, Qiuzhen, Li, Jianqiang, Kay Chen Tan
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 27.02.2023
Schlagworte:	Discriminators Evolutionary algorithms Evolutionary computation Genetic algorithms Machine learning Mopping Multiple objective analysis Optimization Problem solving Scaling up Taxonomy
ISSN:	2331-8422
Online-Zugang:	Volltext
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