Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems

Abstract This paper presents a surrogate-assisted global and distributed local collaborative optimization (SGDLCO) algorithm for expensive constrained optimization problems where two surrogate optimization phases are executed collaboratively at each generation. As the complexity of optimization prob...

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Detalhes bibliográficos

Principais autores:	Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-01-01
coleção:	Scientific Reports
Assuntos:	Surrogate-assisted evolutionary algorithm Expensive constrained optimization problems Global search Local search
Acesso em linha:	https://doi.org/10.1038/s41598-025-85233-6
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