A surrogate-assisted evolutionary algorithm with hypervolume triggered fidelity adjustment for noisy multiobjective integer programming

Although surrogate-assisted evolutionary algorithms (SAEAs) have been widely developed to address computationally expensive multi-objective optimization problems (MOPs), they still encounter difficulties in solving the expensive and noisy combinatorial MOPs. To this end, we propose a novel SAEA to h...

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Vydáno v:	Applied soft computing Ročník 126; s. 109263
Hlavní autoři:	Liu, Shulei, Wang, Handing, Yao, Wen
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.09.2022
Témata:	Fidelity adjustment strategy Multi-fidelity optimization Noisy multiobjective integer programming Surrogate-assisted evolutionary algorithm Surrogate-assisted evolutionary algorithm Multi-fidelity optimization Fidelity adjustment strategy Noisy multiobjective integer programming
ISSN:	1568-4946, 1872-9681
On-line přístup:	Získat plný text
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