Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization
Joint Authors
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-07-31
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A new nonlinear spectral conjugate descent method for solving unconstrained optimization problems is proposed on the basis of the CD method and the spectral conjugate gradient method.
For any line search, the new method satisfies the sufficient descent condition gkTdk<−∥gk∥2.
Moreover, we prove that the new method is globally convergent under the strong Wolfe line search.
The numerical results show that the new method is more effective for the given test problems from the CUTE test problem library (Bongartz et al., 1995) in contrast to the famous CD method, FR method, and PRP method.
American Psychological Association (APA)
Jin-kui, Liu& Jiang, Youyi. 2012. Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization. Abstract and Applied Analysis،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-496416
Modern Language Association (MLA)
Jin-kui, Liu& Jiang, Youyi. Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization. Abstract and Applied Analysis No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-496416
American Medical Association (AMA)
Jin-kui, Liu& Jiang, Youyi. Global Convergence of a Spectral Conjugate Gradient Method for Unconstrained Optimization. Abstract and Applied Analysis. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-496416
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496416