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The conic bundle implementation of the spectral bundle method for large scale semidefinite programming solves in each iteration a semidefinite quadratic subproblem by an interior point approach. For larger cutting model sizes the limiting…

Optimization and Control · Mathematics 2023-08-25 Christoph Helmberg

We introduce a preconditioner based on a hierarchical low-rank compression scheme of Schur complements. The construction is inspired by standard nested dissection, and relies on the assumption that the Schur complements can be approximated,…

Numerical Analysis · Mathematics 2015-09-01 Paolo Gatto , Jan S. Hesthaven

We develop robust solvers for a class of perturbed saddle-point problems arising in the study of a second-order elliptic equation in mixed form (in terms of flux and potential), and of the four-field formulation of Biot's consolidation…

Numerical Analysis · Mathematics 2020-11-11 Wietse M. Boon , Miroslav Kuchta , Kent-Andre Mardal , Ricardo Ruiz-Baier

Due to the indefiniteness and poor spectral properties, the discretized linear algebraic system of the vector Laplacian by mixed finite element methods is hard to solve. A block diagonal preconditioner has been developed and shown to be an…

Numerical Analysis · Mathematics 2016-01-19 Long Chen , Yongke Wu , Lin Zhong , Jie Zhou

In this paper, we introduce a multilevel algorithm for approximating variational formulations of symmetric saddle point systems. The algorithm is based on availability of families of stable finite element pairs and on the availability of…

Numerical Analysis · Mathematics 2013-05-14 Constantin Bacuta

This paper proposes a new parameterized enhanced shift-splitting (PESS) preconditioner to solve the three-by-three block saddle point problem (SPP). Additionally, we introduce a local PESS (LPESS) preconditioner by relaxing the PESS…

Numerical Analysis · Mathematics 2024-11-19 Sk. Safique Ahmad , Pinki Khatun

An effective power based parallel preconditioner is proposed for general large sparse linear systems. The preconditioner combines a power series expansion method with some low-rank correction techniques, where the Sherman-Morrison-Woodbury…

Numerical Analysis · Mathematics 2020-02-04 Qingqing Zheng , Yuanzhe Xi , Yousef Saad

A distributed optimal control problem with the constraint of a linear elliptic partial differential equation is considered. A necessary optimality condition for this problem forms a saddle point system, the efficient and accurate solution…

Numerical Analysis · Mathematics 2013-12-20 Youngsoo Choi , Charbel Farhat , Walter Murray , Michael Saunders

This work describes the development of matrix-free GPU-accelerated solvers for high-order finite element problems in $H(\mathrm{div})$. The solvers are applicable to grad-div and Darcy problems in saddle-point formulation, and have…

Numerical Analysis · Mathematics 2024-11-22 Will Pazner , Tzanio Kolev , Panayot Vassilevski

A combination of block-Jacobi and deflation preconditioning is used to solve a high-order discontinuous collocation-based discretization of the Schur complement of the Poisson-Neumann system as arises in the operator splitting of the…

Numerical Analysis · Mathematics 2016-03-23 Sumedh M. Joshi , Greg N. Thomsen , Peter J. Diamessis

In this paper we discuss optimality conditions for abstract optimization problems over complex spaces. We then apply these results to optimal control problems with a semigroup structure. As an application we detail the case when the state…

Optimization and Control · Mathematics 2019-01-15 M. Soledad Aronna , Frédéric Bonnans , Axel Kröner

The preconditioned iterative solution of large-scale saddle-point systems is of great importance in numerous application areas, many of them involving partial differential equations. Robustness with respect to certain problem parameters is…

Numerical Analysis · Mathematics 2021-04-22 Roland Herzog

We use the practical framework for abstract perturbed saddle point problems recently introduced by Hong et al. to analyze the mixed formulation of the Hodge Laplace problem. We compose two parameter-dependent norms in which the uniform…

Numerical Analysis · Mathematics 2025-08-01 Wietse M. Boon , Johannes Kraus , Tomáš Luber , Maria Lymbery

We consider the generalized successive overrelaxation (GSOR) method for solving a class of block three-by-three saddle-point problems. Based on the necessary and sufficient conditions for all roots of a real cubic polynomial to have modulus…

Numerical Analysis · Mathematics 2024-04-29 Na Huang , Yu-Hong Dai , Dominique Orban , Michael A. Saunders

Complementable operators extend classical matrix decompositions, such as the Schur complement, to the setting of infinite-dimensional Hilbert spaces, thereby broadening their applicability in various mathematical and physical contexts. This…

Functional Analysis · Mathematics 2025-01-14 Sachin Manjunath Naik , P. Sam Johnson

Extended formulations are an important tool in polyhedral combinatorics. Many combinatorial optimization problems require an exponential number of inequalities when modeled as a linear program in the natural space of variables. However, by…

Optimization and Control · Mathematics 2024-06-07 Christoph Buchheim

In this paper, we propose a generalized shift-splitting (GSS) preconditioner, along with its two relaxed variants to solve the double saddle point problem (DSPP). The convergence of the associated GSS iterative method is analyzed, and…

Numerical Analysis · Mathematics 2025-07-08 Sk. Safique Ahmad , Pinki Khatun

This is the third part in a series on a mass conserving, high order, mixed finite element method for Stokes flow. In this part, we study a block-diagonal preconditioner for the indefinite Schur complement system arising from the…

Numerical Analysis · Mathematics 2021-09-30 Mark Ainsworth , Charles Parker

The article is devoted to the development of numerical methods for solving saddle point problems and variational inequalities with simplified requirements for the smoothness conditions of functionals. Recently there were proposed some…

Optimization and Control · Mathematics 2023-11-22 Alexander Titov , Fedor Stonyakin , Mohammad Alkousa , Alexander Gasnikov

We propose a novel preconditioned inexact primal-dual interior point method for constrained convex quadratic programming problems. The algorithm we describe invokes the preconditioned conjugate gradient method on a new reduced Schur…

Numerical Analysis · Mathematics 2021-12-28 Samah Karim , Edgar Solomonik