A clustering-based competitive particle swarm optimization with grid ranking for multi-objective optimization problems

The goal of the multi-objective optimization algorithm is to quickly and accurately find a set of trade-off solutions. This paper develops a clustering-based competitive multi-objective particle swarm optimizer using the enhanced grid for solving multi-objective optimization problems, named EGC-CMOP...

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Detalles Bibliográficos
Autores principales: Ye, Qianlin, Wang, Zheng, Zhao, Yanwei, Dai, Rui, Wu, Fei, Yu, Mengjiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359354/
https://www.ncbi.nlm.nih.gov/pubmed/37474702
http://dx.doi.org/10.1038/s41598-023-38529-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359354/
https://www.ncbi.nlm.nih.gov/pubmed/37474702
http://dx.doi.org/10.1038/s41598-023-38529-4

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