A multi-population evolutionary algorithm based on knowledge transfer for constrained many-objective optimization

Constrained Many-objective Optimization Problems (CMaOPs) are challenging in handling objectives and constraints simultaneously. Here, a novel Constrained Many-objective Optimization Evolutionary Algorithm (CMaOEA) based on Multi-population, Knowledge transfer and Improved environmental selection ca...

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Veröffentlicht in:	Engineering optimization Jg. 57; H. 3; S. 813 - 843
Hauptverfasser:	Ge, Wenlong, Zhang, Shanxin, Song, Weida, Wang, Wei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Abingdon Taylor & Francis 04.03.2025 Taylor & Francis Ltd
Schlagworte:	Algorithms Constrained many-objective optimization Constraints environmental selection evolutionary algorithm Evolutionary algorithms knowledge transfer multi-population Multiple objective analysis Optimization
ISSN:	0305-215X, 1029-0273
Online-Zugang:	Volltext
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