An alternating preconditioner for saddle point problems

Based on matrix splittings, a new alternating preconditioner with two parameters is proposed for solving saddle point problems. Some theoretical analyses for the eigenvalues of the associated preconditioned matrix are given. The choice of the parameters is considered and the quasi-optimal parameters are obtained. The new preconditioner with these quasi-optimal parameters significantly improves the convergence rate of the generalized minimal residual (GMRES) iteration. Numerical experiments from the linearized Navier-Stokes equations demonstrate the efficiency of the new preconditioner, especially on the larger viscosity parameter ν. Further extensions of the preconditioner to generalized saddle point matrices are also checked.     

An extragradient method for finding the saddle point in an optimal control problem

We propose an extragradient method for finding the saddle point of a convex-concave functional defined on solutions of controlled systems of linear ordinary differential equations. We prove the convergence of the method.     

An iterative perturbation method for saddle point problems

An iterative perturbation method is presented for saddle pointproblems a as an iterative scheme for mixed finite element methods.It can be viewed as an extension of augmented Lagrangian methodsto second-order elliptic equations with a reaction term. Thisiterative method can lead to positive definite systems and decouplethe flux variable from the pressure variable. Convergence analysesare established at the differential and finite-dimensional levels.Various computational experiments for problems with continuousand discontinuous coefficients and full diffusion tensors areconducted to confirm the theoretical claims. These experimentsare implemented in the object oriented programming paradigmusing C++ to take advantage of object oriented software engineeringtechniques such as encapsulation, inheritance, and polymorphism.     

An efficient numerical method for preconditioned saddle point problems

In this paper, we consider the solution of linear systems of saddle point type by a preconditioned numerical method. We first transform the original linear system into two sub-systems with small size by a preconditioning strategy, then employ the conjugate gradient (CG) method to solve the linear system with a SPD coefficient matrix, and a splitting iteration method to solve the other sub-system, respectively. Numerical experiments show that the new method can achieve faster convergence than several effective preconditioners published in the recent literature in terms of total runtime and iteration steps.     

鞍点问题的修正对称超松弛迭代算法

为了提高求解鞍点问题的迭代算法的速度,通过设置合适的加速变量,对修正超松弛迭代算法（简记作MSOR-like算法）和广义对称超松弛迭代算法（简记作GSSOR-like算法）进行了修正,给出了修正对称超松弛迭代算法,即MSSOR-like （modified symmetric successiveover-relaxation）算法,并研究了该算法收敛的充分必要条件.最后,通过数值例子表明,选择合适的参数后,新算法的迭代速度和迭代次数均优于MSOR-like （modified successive overrelaxation）和GSSOR-like （generalized symmetric successive over-relaxation）算法,因此,它是一种较好的解决鞍点问题的算法.     

PAHSS-PTS alternating splitting iterative methods for nonsingular saddle point problems

In this paper, we propose the PAHSS-PTS alternating splitting iterative methods for nonsingular saddle point problems. Convergence properties of the proposed methods are studied and corresponding convergence results are given under some suitable conditions. Numerical experiments are presented to confirm the theoretical results, which impliy that PAHSS-PTS iterative methods are effective and feasible.     

关于鞍点问题的预处理HSS-SOR交替分裂迭代方法

为了高效地求解大型稀疏鞍点问题,在白中治,Golub和潘建瑜提出的预处理对称/反对称分裂(PHss)迭代法的基础上,通过结合SOR-like迭代格式对原有迭代算法进行加速,提出了一种预处理HSS-SOR交替分裂迭代方法,并研究了该算法的收敛性.数值例子表明:通过参数值的选择,新算法比SOR-like和PHSS算法都具有更快的收敛速度和更少的迭代次数,选择了合适的参数值后,可以提高算法的收敛效率.     

Regularized extragradient method for finding a saddle point in an optimal control problem

We study n-dimensional cubical pseudomanifolds and their cellular mappings. In particular, we consider a discrete n-cube and all of its (n ? 1)-faces. Then, there exist either one or two or four faces of the cube each of which is mapped onto one face.     

On an iterative method for saddle point problems

Convergence behavior of a nested iterative scheme presented in a paper by Bank, Welfert and Yserentant is studied. It is shown that this scheme converges under conditions weaker than that stated in their paper. Received November 18, 1996 / Revised version received March 18, 1997     

The alternating-direction iterative method for saddle point problems

In the paper, a new alternating-direction iterative method is proposed based on matrix splittings for solving saddle point problems. The convergence analysis for the new method is given. When the better values of parameters are employed, the proposed method has faster convergence rate and less time cost than the Uzawa algorithm with the optimal parameter and the Hermitian and skew-Hermitian splitting iterative method. Numerical examples further show the effectiveness of the method.     

An alternating projections method for certain linear problems in a Hilbert space

Recent extensions of von Neumann's alternating projection methodpermit the computation of proximity projections onto certainconvex sets. This paper exploits this fact in constructing aglobally convergent method for minimizing linear functions overa convex set in a Hilbert space. In particular, we solve theeducational testing problem and an inverse eigenvalue problem,two difficult problems involving positive semidefiniteness constraints.     

Preconditioned AHSS iteration method for singular saddle point problems

In this paper, for solving the singular saddle point problems, we present a new preconditioned accelerated Hermitian and skew-Hermitian splitting (AHSS) iteration method. The semi-convergence of this method and the eigenvalue distribution of the preconditioned iteration matrix are studied. In addition, we prove that all eigenvalues of the iteration matrix are clustered for any positive iteration parameters α and β. Numerical experiments illustrate the theoretical results and examine the numerical effectiveness of the AHSS iteration method served either as a preconditioner or as a solver.     

The corrected Uzawa method for solving saddle point problems

In this paper, we consider the solution of linear systems of saddle point type by correcting the Uzawa algorithm, which has been proposed in [K. Arrow, L. Hurwicz, H. Uzawa, Studies in nonlinear programming, Stanford University Press, Stanford, CA, 1958]. We call this method as corrected Uzawa (CU) method. The convergence of the CU method is analyzed for solving nonsingular saddle point problem as well as the semi‐convergence for the singular case. First, the corrected model for the Uzawa algorithm is established, and the CU algorithm is presented. Then we study the geometric meaning of the CU model. Moreover, we introduce the overall reduction coefficient α to measure the effect of the CU process. It is shown that the CU method converges faster than the Uzawa method and several other methods if the overall reduction coefficient α satisfies certain conditions. Numerical experiments are presented to illustrate the theoretical results and examine the numerical effectiveness of the CU method. Copyright © 2015 John Wiley & Sons, Ltd.     

An extragradient method for equilibrium problems on Hadamard manifolds

In this paper, we propose an extragradient algorithm for solving equilibrium problems on Hadamard manifolds to the case where the equilibrium bifunction is not necessarily pseudomonotone. Under mild assumptions, we establish global convergence results. We show that the multiobjective optimization problem satisfies all the hypotheses of our result of convergence, when formulated as an equilibrium problem.     

Hybrid extragradient method for general equilibrium problems and fixed point problems in Hilbert space

In this paper, we introduce an iterative scheme by the hybrid methods for finding a common element of the set of fixed points of nonexpansive mappings, the set of solutions of an equilibrium problem and the set of solutions of a variational inequality problem in a Hilbert space. Then, we prove the strongly convergent theorem by a hybrid extragradient method to the common element of the set of fixed points of nonexpansive mappings, the set of solutions of an equilibrium problem and the set of solutions of a variational inequality problem. Our results extend and improve the results of Bnouhachem et al. [A. Bnouhachem, M. Aslam Noor, Z. Hao, Some new extragradient iterative methods for variational inequalities, Nonlinear Analysis (2008) doi:10.1016/j.na.2008.02.014] and many others.     

On the UPSS method for non-Hermitian singular saddle point problems

Recently, a new Uzawa-type method, referred as the UPSS method, is proposed for solving the non-Hermitian nonsingular saddle point problems, see Dou, Yang and Wu (2017). In this paper, we give the semi-convergence analysis of the UPSS method when it is used to solve non-Hermitian singular saddle point problems. An example is given to verify the effectiveness of this method for solving non-Hermitian singular saddle point problems.     

A generalized preconditioned HSS method for singular saddle point problems

Li et al. recently studied the generalized HSS (GHSS) method for solving singular linear systems (see Li et al., J. Comput. Appl. Math. 236, 2338–2353 (2012)). In this paper, we generalize the method and present a generalized preconditioned Hermitian and skew-Hermitian splitting method (GPHSS) to solve singular saddle point problems. We prove the semi-convergence of GPHSS under some conditions, and weaken some semi-convergent conditions of GHSS, moreover, we analyze the spectral properties of the corresponding preconditioned matrix. Numerical experiments are given to illustrate the efficiency of GPHSS method with appropriate parameters both as a solver and as a preconditioner.     

On generalized stationary iterative method for solving the saddle point problems

In this paper, the generalized stationary iterative (GSI) method is studied for solving the saddle point problems. The convergence of this method is studied under suitable restrictions on iteration parameters. Numerical example for solving Stokes equation is presented to show the superiority of GSI method.     

A generalized modified SOR-like method for the singular saddle point problems

Recently, Guo et al. proposed a modified SOR-like (MSOR-like) iteration method for solving the nonsingular saddle point problem. In this paper, we further prove the semi-convergence of this method when it is applied to solve the singular saddle point problems under suitable conditions on the involved iteration parameters. Moreover, the optimal iteration parameters and the corresponding optimal semi-convergence factor for the MSOR-like method are determined. In addition, numerical experiments are used to show the feasibility and effectiveness of the MSOR-like method for solving singular saddle point problems, arising from the incompressible flow problems.