Nonlinear Conjugate Gradient Methods with Sufficient Descent Condition for Large-Scale Unconstrained Optimization
Joint Authors
Wei, Zengxin
Xiao, Yun-Hai
Zhang, Jianguo
Source
Mathematical Problems in Engineering
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2009-07-01
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Two nonlinear conjugate gradient-type methods for solving unconstrained optimization problems are proposed.
An attractive property of the methods, is that, without any line search, the generated directions always descend.
Under some mild conditions, global convergence results for both methods are established.
Preliminary numerical results show that these proposed methods are promising, and competitive with the well-known PRP method.
American Psychological Association (APA)
Zhang, Jianguo& Xiao, Yun-Hai& Wei, Zengxin. 2009. Nonlinear Conjugate Gradient Methods with Sufficient Descent Condition for Large-Scale Unconstrained Optimization. Mathematical Problems in Engineering،Vol. 2009, no. 2009, pp.1-16.
https://search.emarefa.net/detail/BIM-456788
Modern Language Association (MLA)
Zhang, Jianguo…[et al.]. Nonlinear Conjugate Gradient Methods with Sufficient Descent Condition for Large-Scale Unconstrained Optimization. Mathematical Problems in Engineering No. 2009 (2009), pp.1-16.
https://search.emarefa.net/detail/BIM-456788
American Medical Association (AMA)
Zhang, Jianguo& Xiao, Yun-Hai& Wei, Zengxin. Nonlinear Conjugate Gradient Methods with Sufficient Descent Condition for Large-Scale Unconstrained Optimization. Mathematical Problems in Engineering. 2009. Vol. 2009, no. 2009, pp.1-16.
https://search.emarefa.net/detail/BIM-456788
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-456788