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2008

Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs

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Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian function and provide an estimate of the optimal active set. In the second phase, an equalityconstrained QP defined by the current inactive variables is approximately minimized in order to generate a second-order search direction. A filter determines the required accuracy of the subproblem solutions and provides an acceptance criterion for the search directions. The resulting algorithm is globally and finitely convergent. The algorithm is suitable for large-scale problems with many degrees of freedom, and provides an alternative to interior-point methods when iterative methods must be used to solve the underlying linear systems. Numerical experiments on a subset of the CUTEr QP test problems demonstrate the effectiveness of the approach. Key words. Large-scale optimization, quadratic programming, gradient-pro...
Michael P. Friedlander, Sven Leyffer
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where SIAMSC
Authors Michael P. Friedlander, Sven Leyffer
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