A class of triangular splitting methods for saddle point problems

In this paper, we study a class of efficient iterative algorithms for the large sparse nonsingular saddle point problems based on the upper and lower triangular (ULT) splitting of the coefficient matrix. We call these algorithms ULT methods. First, the ULT algorithm is established and the characteristic of eigenvalues of the iteration matrix of these new methods is analyzed. Then we give the sufficient and necessary conditions for the convergence of these ULT methods. Moreover, the optimal iteration parameters and the corresponding convergence factors for some special cases of the ULT methods are presented. Numerical experiments on a few model problems are presented to support the theoretical results and examine the numerical effectiveness of these new methods.

[1]  Bing Zheng,et al.  On semi-convergence of parameterized Uzawa methods for singular saddle point problems☆ , 2009 .

[2]  Michael K. Ng,et al.  New preconditioners for saddle point problems , 2006, Appl. Math. Comput..

[3]  Guo-Feng Zhang,et al.  Preconditioned AHSS iteration method for singular saddle point problems , 2013, Numerical Algorithms.

[4]  Jinyun Yuan,et al.  Block SOR methods for rank-deficient least-squares problems , 1998 .

[5]  L. Rudin,et al.  Nonlinear total variation based noise removal algorithms , 1992 .

[6]  Howard C. Elman,et al.  Algorithm 866: IFISS, a Matlab toolbox for modelling incompressible flow , 2007, TOMS.

[7]  J. Y. Yuan,et al.  Preconditioned conjugate gradient method for rank deficient least-squares problems , 1999, Int. J. Comput. Math..

[8]  Howard C. Elman,et al.  Preconditioning for the Steady-State Navier-Stokes Equations with Low Viscosity , 1999, SIAM J. Sci. Comput..

[9]  Gene H. Golub,et al.  Hermitian and Skew-Hermitian Splitting Methods for Non-Hermitian Positive Definite Linear Systems , 2002, SIAM J. Matrix Anal. Appl..

[10]  Andrea Toselli,et al.  Domain decomposition methods : algorithms and theory , 2005 .

[11]  Jun Zou,et al.  Two new variants of nonlinear inexact Uzawa algorithms for saddle-point problems , 2002, Numerische Mathematik.

[12]  Stephen J. Wright Stability of Augmented System Factorizations in Interior-Point Methods , 1997, SIAM J. Matrix Anal. Appl..

[13]  Nira Dyn,et al.  The numerical solution of equality constrained quadratic programming problems , 1983 .

[14]  Gene H. Golub,et al.  Convergence properties of preconditioned Hermitian and skew-Hermitian splitting methods for non-Hermitian positive semidefinite matrices , 2007, Math. Comput..

[15]  Michele Benzi,et al.  Existence and uniqueness of splittings for stationary iterative methods with applications to alternating methods , 1997 .

[16]  Qingqing Zheng,et al.  A class of accelerated Uzawa algorithms for saddle point problems , 2014, Appl. Math. Comput..

[17]  M. Fortin,et al.  Augmented Lagrangian methods : applications to the numerical solution of boundary-value problems , 1983 .

[18]  Gene H. Golub,et al.  A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration , 1999, SIAM J. Sci. Comput..

[19]  Wen Li,et al.  The alternating-direction iterative method for saddle point problems , 2010, Appl. Math. Comput..

[20]  Ting-Zhu Huang,et al.  A modified SSOR iterative method for augmented systems , 2009 .

[21]  Andrew J. Wathen,et al.  Performance and analysis of saddle point preconditioners for the discrete steady-state Navier-Stokes equations , 2002, Numerische Mathematik.

[22]  Ting-Zhu Huang,et al.  Spectral properties of the preconditioned AHSS iteration method for generalized saddle point problems , 2010 .

[23]  Wen Li,et al.  The generalized HSS method for solving singular linear systems , 2012, J. Comput. Appl. Math..

[24]  Gene H. Golub,et al.  Preconditioned Hermitian and skew-Hermitian splitting methods for non-Hermitian positive semidefinite linear systems , 2004, Numerische Mathematik.

[25]  Anil V. Rao,et al.  Practical Methods for Optimal Control Using Nonlinear Programming , 1987 .

[26]  Beresford N. Parlett,et al.  On generalized successive overrelaxation methods for augmented linear systems , 2005, Numerische Mathematik.

[27]  Yimin Wei,et al.  Semi-convergence analysis of Uzawa methods for singular saddle point problems , 2014, J. Comput. Appl. Math..

[28]  Z. Bai,et al.  Restrictively preconditioned conjugate gradient methods for systems of linear equations , 2003 .

[29]  Apostol T. Vassilev,et al.  Analysis of the Inexact Uzawa Algorithm for Saddle Point Problems , 1997 .

[30]  Zeng-Qi Wang,et al.  Restrictive preconditioners for conjugate gradient methods for symmetric positive definite linear systems , 2006 .

[31]  Zeng-Qi Wang,et al.  On parameterized inexact Uzawa methods for generalized saddle point problems , 2008 .

[32]  Zhong-Zhi Bai,et al.  On semi-convergence of Hermitian and skew-Hermitian splitting methods for singular linear systems , 2010, Computing.

[33]  Gene H. Golub,et al.  Numerical solution of saddle point problems , 2005, Acta Numerica.

[34]  Nicholas I. M. Gould,et al.  Constraint Preconditioning for Indefinite Linear Systems , 2000, SIAM J. Matrix Anal. Appl..

[35]  A. Wathen,et al.  Minimum residual methods for augmented systems , 1998 .

[36]  Xiaoqi Yang,et al.  Lagrange-type Functions in Constrained Non-Convex Optimization , 2003 .

[37]  H. H. Rachford,et al.  The Numerical Solution of Parabolic and Elliptic Differential Equations , 1955 .

[38]  Ahmed H. Sameh,et al.  An Efficient Iterative Method for the Generalized Stokes Problem , 1998, SIAM J. Sci. Comput..

[39]  Hai-long Shen,et al.  THE GENERALIZED SOR-LIKE METHOD FOR THE AUGMENTED SYSTEMS , 2006 .

[40]  W. Jason,et al.  アルゴリズム869:ODRPACK95:範囲制約のある重み付け直交距離回帰コード , 2007 .

[41]  Zhong-Zhi Bai,et al.  Optimal parameters in the HSS‐like methods for saddle‐point problems , 2009, Numer. Linear Algebra Appl..

[42]  Eric de Sturler,et al.  Block-Diagonal and Constraint Preconditioners for Nonsymmetric Indefinite Linear Systems. Part I: Theory , 2005, SIAM J. Sci. Comput..

[43]  J. J. Douglas Alternating direction methods for three space variables , 1962 .

[44]  X. Wu,et al.  Conjugate Gradient Method for Rank Deficient Saddle Point Problems , 2004, Numerical Algorithms.

[45]  Alfredo N. Iusem,et al.  Preconditioned conjugate gradient method for generalized least squares problems , 1996 .

[46]  Philip E. Gill,et al.  Practical optimization , 1981 .

[47]  Gene H. Golub,et al.  SOR-like Methods for Augmented Systems , 2001 .

[48]  Gene H. Golub,et al.  Accelerated Hermitian and skew-Hermitian splitting iteration methods for saddle-point problems , 2007 .

[49]  Qingqing Zheng,et al.  On normal and skew-Hermitian splitting iteration methods for large sparse continuous Sylvester equations , 2014, J. Comput. Appl. Math..

[50]  Nicholas I. M. Gould,et al.  On the Solution of Equality Constrained Quadratic Programming Problems Arising in Optimization , 2001, SIAM J. Sci. Comput..

[51]  M. T. Darvishi,et al.  Symmetric SOR method for augmented systems , 2006, Appl. Math. Comput..

[52]  Qingqing Zheng,et al.  A new SOR-Like method for the saddle point problems , 2014, Appl. Math. Comput..

[53]  Junfeng Lu,et al.  A Modified Nonlinear Inexact Uzawa Algorithm with a Variable Relaxation Parameter for the Stabilized Saddle Point Problem , 2010, SIAM J. Matrix Anal. Appl..

[54]  Zhong-Zhi Bai,et al.  Structured preconditioners for nonsingular matrices of block two-by-two structures , 2005, Math. Comput..

[55]  Howard C. Elman,et al.  Fast Nonsymmetric Iterations and Preconditioning for Navier-Stokes Equations , 1996, SIAM J. Sci. Comput..

[56]  G. Golub,et al.  Inexact and preconditioned Uzawa algorithms for saddle point problems , 1994 .