A Conjugate Gradient Algorithm with Function Value Information and N-Step Quadratic Convergence for Unconstrained Optimization

It is generally acknowledged that the conjugate gradient (CG) method achieves global convergence—with at most a linear convergence rate—because CG formulas are generated by linear approximations of the objective functions. The quadratically convergent results are very limited. We introduce a new PRP...

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Detalles Bibliográficos
Autores principales: Li, Xiangrong, Zhao, Xupei, Duan, Xiabin, Wang, Xiaoliang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575111/
https://www.ncbi.nlm.nih.gov/pubmed/26381742
http://dx.doi.org/10.1371/journal.pone.0137166

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575111/
https://www.ncbi.nlm.nih.gov/pubmed/26381742
http://dx.doi.org/10.1371/journal.pone.0137166

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