A new Liu-Storey type nonlinear conjugate gradient method for unconstrained optimization problems

Authors:
Li Zhang
Affiliations:
College of Mathematics and Computational Science, Changsha University of Science and Technology, Changsha 410076, China
Venue:
Journal of Computational and Applied Mathematics
Year:
2009

Citing 7
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Abstract

Although the Liu-Storey (LS) nonlinear conjugate gradient method has a similar structure as the well-known Polak-Ribiere-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.