Improved Grey Wolf Optimization Algorithm and Application

This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wol...

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Detalles Bibliográficos
Autores principales: Hou, Yuxiang, Gao, Huanbing, Wang, Zijian, Du, Chuansheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147573/
https://www.ncbi.nlm.nih.gov/pubmed/35632219
http://dx.doi.org/10.3390/s22103810

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147573/
https://www.ncbi.nlm.nih.gov/pubmed/35632219
http://dx.doi.org/10.3390/s22103810

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