Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients
- Cite this article as:
- Birgin, E.G. & Mario Martínez, J. Computational Optimization and Applications (2002) 23: 101. doi:10.1023/A:1019928808826
- 477 Downloads
A new active-set method for smooth box-constrained minimization is introduced. The algorithm combines an unconstrained method, including a new line-search which aims to add many constraints to the working set at a single iteration, with a recently introduced technique (spectral projected gradient) for dropping constraints from the working set. Global convergence is proved. A computer implementation is fully described and a numerical comparison assesses the reliability of the new algorithm.