Filter methods in nonlinear unconstrained or bound-constrained optimization

Project: PHD

Project Details

Description

The goal of this project is to study filter methods for nonlinear optimization. These methods represent a new class of globalization techniques, that is techniques which guarantee global convergence (i.e. convergence from any starting point) of Newton's method, while impairing the natural efficiency of the underlying local algorithm as little as possible.
StatusFinished
Effective start/end date1/09/0231/08/07

Keywords

  • nonlinear optimization
  • filter methods

Research Output

  • 1 Other report

On the Convergence of a Filter-SQP Algorithm

Fletcher, R., Leyffer, S. & Toint, P., 2000, Namur: FUNDP, Faculté des Sciences. Département de Mathématique. (Technical report; vol. 05)

Research output: Book/Report/JournalOther report