The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-10-16
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
We propose and generalize a new nonlinear conjugate gradient method for unconstrained optimization.
The global convergence is proved with the Wolfe line search.
Numerical experiments are reported which support the theoretical analyses and show the presented methods outperforming CGDESCENT method.
American Psychological Association (APA)
Yueting, Yang& Mingyuan, Cao. 2012. The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-993861
Modern Language Association (MLA)
Yueting, Yang& Mingyuan, Cao. The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization. Journal of Applied Mathematics No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-993861
American Medical Association (AMA)
Yueting, Yang& Mingyuan, Cao. The Global Convergence of a New Mixed Conjugate Gradient Method for Unconstrained Optimization. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-993861
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-993861
