An Opposition-Based Evolutionary Algorithm for Many-Objective Optimization with Adaptive Clustering Mechanism

Balancing convergence and diversity has become a key point especially in many-objective optimization where the large numbers of objectives pose many challenges to the evolutionary algorithms. In this paper, an opposition-based evolutionary algorithm with the adaptive clustering mechanism is proposed...

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Detalles Bibliográficos
Autores principales: Wang, Wan Liang, Li, Weikun, Wang, Yu Le
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525897/
https://www.ncbi.nlm.nih.gov/pubmed/31191632
http://dx.doi.org/10.1155/2019/5126239

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525897/
https://www.ncbi.nlm.nih.gov/pubmed/31191632
http://dx.doi.org/10.1155/2019/5126239

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