A Conjugate Gradient Type Method for the Nonnegative Constraints Optimization Problems
Author
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-10
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
We are concerned with the nonnegative constraints optimization problems.
It is well known that the conjugate gradient methods are efficient methods for solving large-scale unconstrained optimization problems due to their simplicity and low storage.
Combining the modified Polak-Ribière-Polyak method proposed by Zhang, Zhou, and Li with the Zoutendijk feasible direction method, we proposed a conjugate gradient type method for solving the nonnegative constraints optimization problems.
If the current iteration is a feasible point, the direction generated by the proposed method is always a feasible descent direction at the current iteration.
Under appropriate conditions, we show that the proposed method is globally convergent.
We also present some numerical results to show the efficiency of the proposed method.
American Psychological Association (APA)
Li, Can. 2013. A Conjugate Gradient Type Method for the Nonnegative Constraints Optimization Problems. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-513794
Modern Language Association (MLA)
Li, Can. A Conjugate Gradient Type Method for the Nonnegative Constraints Optimization Problems. Journal of Applied Mathematics No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-513794
American Medical Association (AMA)
Li, Can. A Conjugate Gradient Type Method for the Nonnegative Constraints Optimization Problems. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-513794
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-513794