Dai-Kou type conjugate gradient methods with a line search only using gradient

In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical...

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Detalles Bibliográficos
Autores principales: Huang, Yuanyuan, Liu, Changhe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5380739/
https://www.ncbi.nlm.nih.gov/pubmed/28435203
http://dx.doi.org/10.1186/s13660-017-1341-z
Descripción
Sumario:In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical tests and comparisons with the PRP+ conjugate gradient method only using gradient show that the methods are efficient.

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