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A new Liu–Storey type nonlinear conjugate gradient method for unconstrained optimization problems
- Source :
- Journal of Computational and Applied Mathematics. (1):146-157
- Publisher :
- Elsevier B.V.
-
Abstract
- Although the Liu–Storey (LS) nonlinear conjugate gradient method has a similar structure as the well-known Polak–Ribière–Polyak (PRP) and Hestenes–Stiefel (HS) methods, research about this method is very rare. In this paper, based on the memoryless BFGS quasi-Newton method, we propose a new LS type method, which converges globally for general functions with the Grippo–Lucidi line search. Moreover, we modify this new LS method such that the modified scheme is globally convergent for nonconvex minimization if the strong Wolfe line search is used. Numerical results are also reported.
- Subjects :
- Mathematical optimization
Applied Mathematics
Wolfe conditions
Derivation of the conjugate gradient method
Conjugate gradient method
Global convergence
Nonlinear conjugate gradient method
Computational Mathematics
Broyden–Fletcher–Goldfarb–Shanno algorithm
Nonconvex function
Quasi-Newton method
Conjugate residual method
Applied mathematics
Gradient method
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 03770427
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Journal of Computational and Applied Mathematics
- Accession number :
- edsair.doi.dedup.....7940e7f0770d904a3374df53e2795f43
- Full Text :
- https://doi.org/10.1016/j.cam.2008.07.016