We develop and compare multilevel algorithms for solving constrained nonlinear variational problems via interior point methods. Several equivalent formulations of the linear systems arising at each iteration of the interior point method are compared from the point of view of conditioning and iterative solution. Furthermore, we show how a multilevel continuation strategy can be used to obtain good initial guesses ("hot starts") for each nonlinear iteration. Some minimal surface and volume-constrained image registration problems are used to illustrate the various approaches. © 2009 Society for Industrial and Applied Mathematics.

Multilevel algorithms for large-scale interior point methods

Benzi, Michele;
2009

Abstract

We develop and compare multilevel algorithms for solving constrained nonlinear variational problems via interior point methods. Several equivalent formulations of the linear systems arising at each iteration of the interior point method are compared from the point of view of conditioning and iterative solution. Furthermore, we show how a multilevel continuation strategy can be used to obtain good initial guesses ("hot starts") for each nonlinear iteration. Some minimal surface and volume-constrained image registration problems are used to illustrate the various approaches. © 2009 Society for Industrial and Applied Mathematics.
2009
Constrained optimization; Inexact newton; Krylov methods; Multigrid; Preconditioning; Saddle point problems; Applied Mathematics; Computational Mathematics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/75325
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