We address the iterative solution of KKT systems arising in the solution of convex quadratic programming problems. Two strictly related and well established formulations for such systems are studied with particular emphasis on the effect of preconditioning strategies on their relation. Constraint and augmented preconditioners are considered, and the choice of the augmentation matrix is discussed. A theoretical and experimental analysis is conducted to assess which of the two formulations should be preferred for solving large-scale problems.
Morini, B., Simoncini, V., Tani, M. (2017). A comparison of reduced and unreduced KKT systems arising from interior point methods. COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 68(1), 1-27 [10.1007/s10589-017-9907-8].
A comparison of reduced and unreduced KKT systems arising from interior point methods
Simoncini, Valeria;
2017
Abstract
We address the iterative solution of KKT systems arising in the solution of convex quadratic programming problems. Two strictly related and well established formulations for such systems are studied with particular emphasis on the effect of preconditioning strategies on their relation. Constraint and augmented preconditioners are considered, and the choice of the augmentation matrix is discussed. A theoretical and experimental analysis is conducted to assess which of the two formulations should be preferred for solving large-scale problems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
