A multi-objective evolutionary algorithm for steady-state constrained multi-objective optimization problems

Many multi-objective evolutionary algorithms (MOEAs) are developed to solve constrained multi-objective optimization problems (CMOPs). However, they encounter low efficiency for steady-state CMOPs which are to optimize a known feasible solution named the current steady-state operation point. This pa...

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Vydáno v:	Applied soft computing Ročník 101; s. 107042
Hlavní autoři:	Yang, Yongkuan, Liu, Jianchang, Tan, Shubin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.03.2021
Témata:	Co-evolution Multi-objective evolutionary algorithm Steady-state constrained multi-objective optimization Multi-objective evolutionary algorithm Steady-state constrained multi-objective optimization Co-evolution
ISSN:	1568-4946, 1872-9681
On-line přístup:	Získat plný text
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