| Article ID: | iaor20042272 |
| Country: | Singapore |
| Volume: | 20 |
| Issue: | 2 |
| Start Page Number: | 275 |
| End Page Number: | 284 |
| Publication Date: | Nov 2003 |
| Journal: | Asia-Pacific Journal of Operational Research |
| Authors: | Shi Zhen-Jun |
| Keywords: | programming: nonlinear |
The paper presents a new memory gradient method for unconstrained optimization problem, and proves the convergence of the algorithm under exact line searches. The linear convergence rate is investigated when the objective function is uniformly convex. Numerical experiments show that the new algorithm is very effective in practice.