A self-organizing assisted multi-task algorithm for constrained multi-objective optimization problems

Constrained multi-objective optimization problems (CMOPs) require a delicate balance between satisfying constraints and optimizing objectives. Existing constrained multi-objective evolutionary algorithms (CMOEAs) often struggle to balance convergence, diversity, and feasibility, especially when deal...

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Veröffentlicht in:	Information sciences Jg. 664; S. 120339
Hauptverfasser:	Ye, Qianlin, Wang, Wanliang, Li, Guoqing, Dai, Rui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.04.2024
Schlagworte:	Constrained multi-objective optimization Constraint-to-constraint Multi-task Self-organizing mapping Constrained multi-objective optimization Constraint-to-constraint Multi-task Self-organizing mapping
ISSN:	0020-0255, 1872-6291
Online-Zugang:	Volltext
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