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...

Celý popis

Podrobná bibliografie

Vydáno v:	Information sciences Ročník 561; s. 304 - 325
Hlavní autoři:	Pan, Jeng-Shyang, Liu, Nengxian, Chu, Shu-Chuan, Lai, Taotao
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Inc 01.06.2021
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!