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On the superlinear local convergence of a filter-SQP method

Stefan Ulbrich (sulbrich***at***ma.tum.de)

Abstract: Transition to superlinear local convergence is shown for a modified version of the trust-region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and Toint [8]. Hereby, the original trust-region SQP-steps can be used without an additional second order correction. The main modification consists in using the Lagrangian function value instead of the objective function value in the filter together with an appropriate infeasibility measure. Moreover, it is shown that the modified trust-region filter-SQP method has the same global convergence properties as the original algorithm in [8].

Keywords: nonlinear programming, superlinear convergence, global convergence, filter, SQP

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Citation: Technical Report, Zentrum Mathematik, Technische Universitaet Muenchen, Boltzmannstr. 3, 85747 Garching b. Muenchen, Germany, October 2002.

Download: [Postscript][Compressed Postscript][PDF]

Entry Submitted: 10/24/2002
Entry Accepted: 10/24/2002
Entry Last Modified: 10/24/2002

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