基于GMRES的多项式预处理广义极小残差法

求解大型稀疏线性方程组一般采用迭代法,其中GMRES(m)算法是一种非常有效的算法,然而该算法在解方程组时,可能发生停滞．为了克服算法GMRES(m)解线性系统Ax=b过程中可能出现的收敛缓慢或不收敛,本文利用GMRES本身构造出一种有效的多项式预处理因子pk(z),该多项式预处理因子非常简单且易于实现．数值试验表明,新算法POLYGMRES(m)较好地克服了GMRES(m)的缺陷．     

求解PageRank问题的重启GMRES修正的多分裂迭代法

PageRank算法已经成为网络搜索引擎的核心技术。针对PageRank问题导出的线性方程组,首先将Krylov子空间方法中的重启GMRES(generalized minimal residual)方法与多分裂迭代(multi-splitting iteration,MSI)方法相结合,提出了一种重启GMRES修正的多分裂迭代法;然后,给出了该算法的详细计算流程和收敛性分析;最后,通过数值实验验证了该算法的有效性。     

求解伪单调变分不等式的两种投影算法

本文提出了两种求解伪单调变分不等式的定步长的投影算法．这与Solodov ＆ Tseng(1996)和He(1997)的变步长策略不同．我们证明了算法的全局收敛性，并且还在一定条件下证明了算法的Q-线性收敛性．     

红黑排序混合算法收敛速度分析

The algorithm of applying the block Gauss elimination to the Red-Black or-dering matrix to reduce the order of the system then solve the reduced system byiterative methods is called Hybrid Red-Black Ordering algorithm.In this paper,we discuss the convergence rate of the hybrid methods combined with JACOBI,CG,GMRES(m).Theoretical analysis shows that without preconditioner thesethree hybrid methods converge about 2 times as fast as the corresponding natural ordering methods.For the case that all the eigenvalues is near the real axis, the GMRES(m) algorithm converges about 3 times faster than the natural ordering GMRES(m).Various numerical experiments are presented.For large scale prob-lem with preconditioners, numerical experiments show that the GMRES(m) hybrid methods converge from about 3 times to even 5 times as fast as the natural order-ing methods and the computing time is reduced to about 1/3 even 1/6 of that of the natural ordering methods.     

分裂可行问题(SFP)的投影算法

本文探讨了分裂可行问题(SFP)的投影算法．我们先定义了(SFP)的反问题(ISFP), 然后利用正交投影性质,给出了(SFP)与(ISFP)及某些投影不动点问题之间的关系．随后, 给出了求解(SFP)的几种正交投影算法,其中包括精确和不精确投影格式．基于变分不等式中投影算法收敛性的证明思路和分裂可行问题的特有形式,证明了这几种算法的收敛性．最后通过几个算例对讨论的方法进行了初步比较．     

求可测函数的总体极小值方法的收敛性分析

[1]中提出了求解连续函数f(x)总体极小值的均值算法，并证明了算法的全局收敛性．若假设f(t)是定义在某可测集G上的可测函数，本证明了均值算法产生的迭代序列全局收敛到f(t)的本质极小值，若进一步假设函数f(t)满足测度Lipschitz条件，还证明了求可测函数的均值算法是线性收敛的．     

非线性互补问题的一种不可行非内点连续算法

基于Chen-Harker—Kanzow-Smale光滑函数，对单调非线性互补问题NCP(f)给出了一种不可行非内点连续算法，该算法在每次迭代时只需求解一个线性等式系统，执行一次线搜索，算法在NCP(f)的解处不需要严格互补的条件下，具有全局线性收敛性和局部二次收敛性．     

快速多极边界元法解的存在唯一性

本对求解3维弹性摩擦接触问题的快速多极边界元法(FM—BEM)在数学理论上作了深入探讨．首先，利用向量和子空间理论找出快速优化广义极小残余算法(GMRES(m))求解边界元方程组所满足的代数条件．使对工程用FM—BEM解的研究转化为对代数问题的讨论，然后．分三步证明了FM-BEM解的存在唯一性，为FM-BEM求解弹性摩擦接触工程问题提供强有力的数学支撑．     

不等式约束优化问题的一个势函数

基于Carroll(1961)建立的罚函数，本文给出了不等式约束优化问题的一个势函数，并且讨论了该函数的性质．最后证明了在此基础上建立的对偶算法具有Q-线性收敛性．     

有界约束单调变分不等式的内点连续算法

讨论变分不等式问题VIP(X，F)，其中F是单调函数，约束集X为有界区域．利用摄动技术和一类光滑互补函数将问题等价转化为序列合两个参数的非线性方程组，然后据此建立VIP(X，F)的一个内点连续算法．分析和论证了方程组解的存在性和惟一性等重要性质，证明了算法很好的整体收敛性，最后对算法进行了初步的数值试验。     

二维Helmholtz方程的联合紧致差分离散方程组的预处理方法

对于二维的Helmholtz方程,本文用联合紧致差分格式(CCD)离散,该差分格式具有六阶精度,三点差分和隐式的特点.本文基于CCD格式离散得到的线性系统和循环矩阵的快速傅里叶变换,提出了一种循环型预处理算子用于广义极小残量迭代算法(GMRES).给出了循环型预处理子的求解算法,证明了该预处理算子能使迭代算法具有较快的收敛速度.本文还与其他算法的预处理算子作比较,数值结果表明本文提出的循环型预处理算子具有更好的稳定性,并且对于较大的波数k,收敛速度也更快.     

A PRODUCT HYBRID GMRES ALGORITHM FOR NONSYMMETRIC LINEAR SYSTEMS

It has been observed that the residual polynomials resulted from successive restarting cycles of GMRES(m) may differ from one another meaningfully. In this paper, it is further shown that the polynomials can complement one another harmoniously in reducing the iterative residual. This characterization of GMRES(m) is exploited to formulate an efficient hybrid iterative scheme, which can be widely applied to existing hybrid algorithms for solving large nonsymmetric systems of linear equations. In particular, a variant of the hybrid GMRES algorithm of Nachtigal, Reichel and Trefethen (1992) is presented. It is described how the new algorithm may offer significant performance improvements over the original one.     

Optimal Control of Iterative Solution Methods for Linear Systems of Equations

Iterative solution methods for linear systems of equations can be regarded as discrete-time control systems, for which a stabilizing feedback control has to be found. Well known algorithms such as GMRES(m) may exhibit unstable dynamics or sensitive dependence on initial conditions, thus preventing the algorithm to converge to the desired solution. Based on linear system feedback design techniques a new algorithm is proposed that does not suffer under such shortcomings. Global convergence to the desired solution is shown for any initial state. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

M/M/c休假排队系统稳态分布的数值计算

从数值计算角度研究M/M/c休假排队系统稳定状态的概率分布.采用GMRES方法求解概率分布向量所满足的大型线性方程,构造了一个循环预处理算子加速GMRES方法的收敛.数值实例验证了该算法的优越性.     

A Convergence Analysis of Gmres and Fom Methods for Sylvester Equations

We discuss convergence properties of the GMRES and FOM methods for solving large Sylvester equations of the form AX–XB=C. In particular we show the importance of the separation between the fields of values of A and B on the convergence behavior of GMRES. We also discuss the stagnation phenomenon in GMRES and its consequence on FOM. We generalize the issue of breakdown in the block-Arnoldi algorithm and explain its consequence on FOM and GMRES methods. Several numerical tests illustrate the theoretical results.     

On the convergence behavior of the restarted GMRES algorithm for solving nonsymmetric linear systems

The solution of nonsymmetric systems of linear equations continues to be a difficult problem. A main algorithm for solving nonsymmetric problems is restarted GMRES. The algorithm is based on restarting full GMRES every s iterations, for some integer s>0. This paper considers the impact of the restart frequency s on the convergence and work requirements of the method. It is shown that a good choice of this parameter can lead to reduced solution time, while an improper choice may hinder or preclude convergence. An adaptive procedure is also presented for determining automatically when to restart. The results of numerical experiments are presented.     

Some observations on weighted GMRES

We investigate the convergence of the weighted GMRES method for solving linear systems. Two different weighting variants are compared with unweighted GMRES for three model problems, giving a phenomenological explanation of cases where weighting improves convergence, and a case where weighting has no effect on the convergence. We also present a new alternative implementation of the weighted Arnoldi algorithm which under known circumstances will be favourable in terms of computational complexity. These implementations of weighted GMRES are compared for a large number of examples. We find that weighted GMRES may outperform unweighted GMRES for some problems, but more often this method is not competitive with other Krylov subspace methods like GMRES with deflated restarting or BICGSTAB, in particular when a preconditioner is used.