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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Veröffentlicht in:	Applied soft computing Jg. 126; S. 109263
Hauptverfasser:	Liu, Shulei, Wang, Handing, Yao, Wen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.09.2022
Schlagworte:	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
Online-Zugang:	Volltext
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