An efficient surrogate-assisted hybrid optimization algorithm for expensive optimization problems

Surrogate-assisted evolutionary algorithms (SAEAs) are potential approaches to solve computationally expensive optimization problems. The critical idea of SAEAs is to combine the powerful searching capabilities of evolutionary algorithms with the predictive capabilities of surrogate models. In this...

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Bibliographic Details

Published in:	Information sciences Vol. 561; pp. 304 - 325
Main Authors:	Pan, Jeng-Shyang, Liu, Nengxian, Chu, Shu-Chuan, Lai, Taotao
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.06.2021
Subjects:	Differential evolution Expensive problems Hybrid optimization algorithm Surrogate-assisted Teaching-learning-based optimization Differential evolution Hybrid optimization algorithm Surrogate-assisted Teaching-learning-based optimization Expensive problems
ISSN:	0020-0255, 1872-6291
Online Access:	Get full text
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