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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Bibliographic Details
Published in:Applied soft computing Vol. 126; p. 109263
Main Authors: Liu, Shulei, Wang, Handing, Yao, Wen
Format: Journal Article
Language:English
Published: Elsevier B.V 01.09.2022
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ISSN:1568-4946, 1872-9681
Online Access:Get full text
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