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An efficient modified Polak–Ribière–Polyak conjugate gradient method with global convergence properties.
- Source :
- Optimization Methods & Software; December 2017, Vol. 32 Issue 6, p1299-1312, 14p
- Publication Year :
- 2017
-
Abstract
- The conjugate gradient (CG) method is one of the most popular methods for solving large-scale unconstrained optimization problems. In this paper, a new modified version of the CG formula that was introduced by Polak, Ribière, and Polyak is proposed for problems that are bounded below and have a Lipschitz-continuous gradient. The new parameter provides global convergence properties when the strong Wolfe-Powell (SWP) line search or the weak Wolfe-Powell (WWP) line search is employed. A proof of a sufficient descent condition is provided for the SWP line search. Numerical comparisons between the proposed parameter and other recent CG modifications are made on a set of standard unconstrained optimization problems. The numerical results demonstrate the efficiency of the proposed CG parameter compared with the other CG parameters. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 10556788
- Volume :
- 32
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- Optimization Methods & Software
- Publication Type :
- Academic Journal
- Accession number :
- 125480741
- Full Text :
- https://doi.org/10.1080/10556788.2016.1266354