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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Surrogate-assisted evolutionary algorithm
Expensive constrained optimization problems
Global search
Local search
Online Access:https://doi.org/10.1038/s41598-025-85233-6
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-85233-6

Similar Items