A decomposition-based evolutionary algorithm for scalable multi/many-objective optimization

The aim of evolutionary multi/many-objective optimization is to obtain a set of Pareto-optimal solutions with good trade-off among the multiple conflicting objectives. However, the convergence and diversity of multiobjective evolutionary algorithms often seriously decrease with the number of objecti...

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Veröffentlicht in:	Memetic computing Jg. 13; H. 3; S. 413 - 432
Hauptverfasser:	Chen, Jiaxin, Ding, Jinliang, Tan, Kay Chen, Chen, Qingda
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2021 Springer Nature B.V
Schlagworte:	Applications of Mathematics Artificial Intelligence Bioinformatics Complex Systems Control Decomposition Engineering Evolutionary algorithms Genetic algorithms Mathematical and Computational Engineering Mechatronics Multiple objective analysis Optimization Regular Research Paper Resource allocation Robotics Search methods Search process Decomposition-based evolutionary algorithm Bidirectional local search Many-objective optimization Multiobjective optimization Multioperator and multiparameter Resource allocation
ISSN:	1865-9284, 1865-9292
Online-Zugang:	Volltext
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