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A filter-trust-region method for unconstrained optimization

Nick Gould (n.gould***at***rl.ac.uk)
Caroline Sainvitu (caroline.sainvitu***at***fundp.ac.be)
Philippe Toint (philippe.toint***at***fundp.ac.be)

Abstract: A new filter-trust-region algorithm for solving unconstrained nonlinear optimization problems is introduced. Based on the filter technique introduced by Fletcher and Leyffer, it extends an existing technique of Gould, Leyffer and Toint (SIAM J. Optim., to appear 2004) for nonlinear equations and nonlinear least-squares to the fully general unconstrained optimization problem. The new algorithm is shown to be globally convergent to at least one second-order critical point, and numerical experiments indicate that it is very competitive with more classical trust-region algorithms.

Keywords: nonlinear unconstrained optimization, filter methods

Category 1: Nonlinear Optimization (Unconstrained Optimization )

Category 2: Nonlinear Optimization (Nonlinear Systems and Least-Squares )

Citation: Report 04/03, Department of Mathematics, Univeristy of Namur, Namur, Belgium

Download: [Postscript]

Entry Submitted: 02/05/2004
Entry Accepted: 02/05/2004
Entry Last Modified: 02/05/2004

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