Article ID: | iaor19981343 |
Country: | Netherlands |
Volume: | 6 |
Issue: | 2 |
Start Page Number: | 117 |
End Page Number: | 136 |
Publication Date: | Sep 1996 |
Journal: | Computational Optimization and Applications |
Authors: | Ferris Michael C., Lucidi Stefano, Roma Massimo |
We present a new algorithmic framework for solving unconstrained minimization problems that incorporates a curvilinear linesearch. The search direction used in our framework is a combination of an approximate Newton direction and a direction of negative curvature. Global convergence to a stationary point where the Hessian matrix is positive semidefinite is exhibited for this class of algorithms by means of a nonmonotone stabilization strategy. An implementation using the Bunch–Parlett decomposition is shown to outperform several other techniques on a large class of test problems.