A two-stage dominance-based surrogate-assisted evolution algorithm for high-dimensional expensive multi-objective optimization

In the past decades, surrogate-assisted evolutionary algorithms (SAEAs) have become one of the most popular methods to solve expensive multi-objective optimization problems (EMOPs). However, most existing methods focus on low-dimensional EMOPs because a large number of training samples are required...

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Detalles Bibliográficos
Autores principales: Yu, Mengjiao, Wang, Zheng, Dai, Rui, Chen, Zhongkui, Ye, Qianlin, Wang, Wanliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423721/
https://www.ncbi.nlm.nih.gov/pubmed/37574501
http://dx.doi.org/10.1038/s41598-023-40019-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423721/
https://www.ncbi.nlm.nih.gov/pubmed/37574501
http://dx.doi.org/10.1038/s41598-023-40019-6

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