A preconditioning technique for a class of PDE-constrained optimization problems


DOI: 10.1007/s10444-011-9173-8

Cite this article as:
Benzi, M., Haber, E. & Taralli, L. Adv Comput Math (2011) 35: 149. doi:10.1007/s10444-011-9173-8


We investigate the use of a preconditioning technique for solving linear systems of saddle point type arising from the application of an inexact Gauss–Newton scheme to PDE-constrained optimization problems with a hyperbolic constraint. The preconditioner is of block triangular form and involves diagonal perturbations of the (approximate) Hessian to insure nonsingularity and an approximate Schur complement. We establish some properties of the preconditioned saddle point systems and we present the results of numerical experiments illustrating the performance of the preconditioner on a model problem motivated by image registration.


Constrained optimizationKKT conditionsSaddle point problemsHyperbolic PDEsKrylov subspace methodsPreconditioningMonge–Kantorovich problemImage registration

Mathematics Subject Classifications (2010)


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© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  1. 1.Department of Mathematics and Computer ScienceEmory UniversityAtlantaUSA
  2. 2.Department of MathematicsUniversity of British ColumbiaVancouverCanada
  3. 3.Quantitative Analytics Research GroupStandard & Poor’sNew YorkUSA