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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Vydané v:	Engineering optimization Ročník 57; číslo 3; s. 813 - 843
Hlavní autori:	Ge, Wenlong, Zhang, Shanxin, Song, Weida, Wang, Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Taylor & Francis 04.03.2025 Taylor & Francis Ltd
Predmet:	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
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