Computational Optimization and Applications

, Volume 23, Issue 1, pp 101–125

Large-Scale Active-Set Box-Constrained Optimization Method with Spectral Projected Gradients

  • Ernesto G. Birgin
  • José Mario Martínez
Article

DOI: 10.1023/A:1019928808826

Cite this article as:
Birgin, E.G. & Mario Martínez, J. Computational Optimization and Applications (2002) 23: 101. doi:10.1023/A:1019928808826

Abstract

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.

box-constrained minimizationnumerical methodsactive-set strategiesSpectral Projected Gradient

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Ernesto G. Birgin
    • 1
  • José Mario Martínez
    • 2
  1. 1.Department of Computer Science IME-USPUniversity of São PauloSão Paulo SPBrazil
  2. 2.Department of Applied Mathematics IMECC-UNICAMPUniversity of CampinasCampinas SPBrazil