A reference vector based multiobjective evolutionary algorithm with Q-learning for operator adaptation

Maintaining a balance between convergence and diversity is a challenge for multiobjective evolutionary optimization. As crossover operators can affect the offspring distribution, an adaptive operator selection and reference vector based evolutionary algorithm (OVEA) for multiobjective optimization i...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 76; S. 101225
Hauptverfasser:	Jiao, Keming, Chen, Jie, Xin, Bin, Li, Li
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.02.2023
Schlagworte:	Adaptive operator selection Multiobjective evolutionary algorithm Q-learning Reference vector Q-learning Adaptive operator selection Multiobjective evolutionary algorithm Reference vector
ISSN:	2210-6502
Online-Zugang:	Volltext
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