Clustering-Aided Grid-Based One-to-One Selection-Driven Evolutionary Algorithm for Multi/Many-Objective Optimization

Multiobjective evolutionary algorithms are highly effective in solving multiobjective optimization problems (MOPs). The selection strategy, involving mating and environmental selection, is crucial in shaping these algorithms. However, when applied to many-objective optimization (MaOPs) with more tha...

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Detalhes bibliográficos

Principais autores:	Vikas Palakonda, Jae-Mo Kang, Heechul Jung
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2024-01-01
coleção:	IEEE Access
Assuntos:	Convergence diversity multi-objective optimization many-objective optimization K-means clustering grid settings
Acesso em linha:	https://ieeexplore.ieee.org/document/10522659/
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