外推的MHSS迭代法求解一类大型稀疏的复对称线性系统

本文对改良的Hermitian和反Hermitian分裂迭代方法 (MHSS)使用了外推技术,构造了外推的MHSS(EMHSS)迭代法.从理论上给出了EMHSS迭代方法的迭代矩阵与MHSS迭代方法的迭代矩阵之间的关系,并讨论了EMHSS迭代方法的收敛条件.最后用数值实验验证了所提方法的有效性.     

线性方程组的异步松弛迭代法*

本文考虑解线性方程组经典迭代法的异步形式,对系数矩阵为H矩阵,给出了异步迭代过程收敛性的充分条件,这不仅降低了文献[3]对系数矩阵的要求,而且收敛区域比文献[3]的大.     

求解正定线性方程组的具有共轭性的并行多分裂迭代法（英文）

本文结合具有共轭性的一种特殊多分裂与系数矩阵的稀疏性,提出求解系数矩阵为正定矩阵的线性方程组的并行多分裂迭代法.我们的新迭代法与标准迭代法不同点有两个方面:一是在我们的多分裂方法中只要求其中之一是收敛的分裂;二是权矩阵不必预先给出.这在并行计算中是很有效的算法.最后以数值实验验证新方法的有效性和可行性.     

求解线性系统的广义二阶段多分裂迭代法的收敛性

一般二阶段多分裂迭代法的权矩阵都是预先给出的,在迭代过程中并不知道它的优劣.提出了广义的二阶段多分裂迭代法,它的加权矩阵不必预先给出,而是在迭代过程中通过求超平面上的最优解而得出的随迭代步数变化的动态的权矩阵.这样,动态的权矩阵能使得第k步的近似解更加逼近问题的真解.文中建立了新方法的收敛性理论,并以数值实验验证新方法的有效性.     

求解一类非线性互补问题的松弛two-sweep模系矩阵分裂迭代法

本文构造了求解一类非线性互补问题的松弛two-sweep模系矩阵分裂迭代法. 理论分析建立了新方法在系数矩阵为正定矩阵或H₊矩阵时的收敛性质．数值实验结果表明新方法是行之有效的, 并且在最优参数下松弛two-sweep模系矩阵分裂迭代法在迭代步数和时间上均优于传统的模系矩阵分裂迭代法和two-sweep模系矩阵分裂迭代法.     

H-矩阵线性方程组的一类预条件并行多分裂SOR迭代法

基于并行多分裂算法的思想及SOR迭代格式, 本文提出一种求解H-矩阵线性方程组新的并行多分裂SOR迭代法, 新方法某种程度上避免了SOR迭代法中选取最优参数的困难. 同时, 选取Kohno等(1997)提出的预条件子$P=I+S_{\alpha}$对原始线性方程组进行预处理, 进而给出了一种实用的预条件并行多分裂SOR迭代法. 理论分析和数值实验均表明, 新算法是实用而有效的.     

H-矩阵非线性互补问题基于模的矩阵分裂迭代法改进的收敛性定理北大核心CSCD

该文在较弱的条件下,证明了解一类H-矩阵非线性互补问题基于模的矩阵分裂迭代法和相应的加速迭代法的收敛性定理.这意味着对于分裂A=M-N有更多的选择,使得基于模的矩阵分裂迭代法得以收敛.改进的收敛性定理扩展了基于模的矩阵分裂迭代法的应用范围.     

M-矩阵线性互补问题模系多分裂迭代方法的收敛性

首先证明了M-矩阵的H-相容分裂都是正则分裂,反之不成立.这表明对于M-矩阵而言,其正则分裂包含H-相容分裂.然后针对系数矩阵为M-矩阵的线性互补问题,建立了两个收敛定理:一是模系多分裂迭代方法关于正则分裂的收敛定理;二是模系二级多分裂迭代方法关于外迭代为正则分裂和内迭代为弱正则分裂的收敛定理.     

对称正定Toeplitz方程组的多级迭代求解

二级迭代法亦称内外迭代法. 多级迭代法由多个二级迭代嵌套而成.这些方法特别适合于并行计算,同时可以理解为古典迭代法的延伸或共轭梯度法的预处理子.本文讨论了对称正定Toeplitz线性方程组多级迭代法. 首先,基于Toeplitz矩阵的结构, 我们给出了多级块Jacobi分裂,然后证明了每一级分裂均为P-正则分裂, 并证明了当每一级内迭代次数均为偶数时,迭代法的收敛性. 最后通过数值实例验证了此方法的有效性.     

关于Leontief产出方程的二级分裂迭代方法

研究Leontief投入产出模型中计算产出向量的迭代方法,基于Leontief产出方程,在矩阵规模很大,直接计算逆矩阵很困难的条件下,通过引入参数并运用二级分裂迭代思想和松弛技术,提出了Leontief产出方程的二级分裂迭代方法,给出了该方法的收敛理论.利用给出的收敛因子的计算方法,讨论了参数的优化选择,数值实例验证了此方法的有效性,表明优化参数能有效提高迭代方法的收敛效率.     

EXPERIMENTAL STUDY OF THE ASYNCHRONOUS MULTISPLITTING RELAXATION METHODS FOR THE LINEAR COMPLEMENTARITY PROBLEMS

We study the numerical behaviours of the relaxed asynchronous multisplitting methods for the linear complementarity problems by solving some typical problems from practical applications on a real multiprocessor system. Numerical results show that the parallel multisplitting relaxation methods always perform much better than the corresponding sequential alternatives, and that the asynchronous multisplitting relaxation methods often outperform their corresponding synchronous counterparts. Moreover, the two-sweep relaxed multisplitting methods have better convergence properties than their corresponding one-sweep relaxed ones in the sense that they have larger convergence domains and faster convergence speeds. Hence, the asynchronous multisplitting unsymmetric relaxation iterations should be the methods of choice for solving the large sparse linear complementarity problems in the parallel computing environments.     

A NEW GENERALIZED ASYNCHRONOUS PARALLEL MULTISPLITTING ITERATION METHOD

1.IntroductionTosolvelargesparsesystemsoflinearandnonlinearequationsonthemultiprocessorsystems,manyauthorspresentedandstudiedvariousparalleliterativemethodsinthesenseofmultisplittinginrecentyears.FOrdetailsonecanreferto[1]-[9]andreferencestherein.Amo...     

Asynchronous Multisplitting GAOR Method and Asynchronous Multisplitting SSOR Method for Systems of Weakly Nonlinear Equations

In this article, we introduce two new asynchronous multisplitting methods for solving the system of weakly nonlinear equations Ax = G(x) in which A is an n × n real matrix and G(x) = (g ₁(x), g ₂(x), . . . , g _n (x)) ^T is a P-bounded mapping. First, by generalized accelerated overrelaxation (GAOR) technique, we introduce the asynchronous parallel multisplitting GAOR method (including the synchronous parallel multisplitting AOR method as a special case) for solving the system of weakly nonlinear equations. Second, asynchronous parallel multisplitting method based on symmetric successive overrelaxation (SSOR) multisplitting is introduced, which is called asynchronous parallel multisplitting SSOR method. Then under suitable conditions, we establish the convergence of the two introduced methods. The given results contain synchronous multisplitting iterations as a special case.     

A class of asynchronous parallel nonlinear accelerated overrelaxation methods for the nonlinear complementarity problems

In accordance with the principle of using sufficiently the delayed information, and by making use of the nonlinear multisplitting and the nonlinear relaxation techniques, we present in this paper a class of asynchronous parallel nonlinear multisplitting accelerated overrelaxation (AOR) methods for solving the large sparse nonlinear complementarity problems on the high-speed MIMD multiprocessor systems. These new methods, in particular, include the so-called asynchronous parallel nonlinear multisplitting AOR-Newton method, the asynchronous parallel nonlinear multisplitting AOR-chord method and the asynchronous parallel nonlinear multisplitting AOR-Steffensen method. Under suitable constraints on the nonlinear multisplitting and the relaxation parameters, we establish the local convergence theory of this class of new methods when the Jacobi matrix of the involved nonlinear mapping at the solution point of the nonlinear complementarity problem is an H-matrix.     

Two-Stage Multisplitting Iteration Methods Using Modulus-Based Matrix Splitting as Inner Iteration for Linear Complementarity Problems

The matrix multisplitting iteration method is an effective tool for solving large sparse linear complementarity problems. However, at each iteration step we have to solve a sequence of linear complementarity sub-problems exactly. In this paper, we present a two-stage multisplitting iteration method, in which the modulus-based matrix splitting iteration and its relaxed variants are employed as inner iterations to solve the linear complementarity sub-problems approximately. The convergence theorems of these two-stage multisplitting iteration methods are established. Numerical experiments show that the two-stage multisplitting relaxation methods are superior to the matrix multisplitting iteration methods in computing time, and can achieve a satisfactory parallel efficiency.     

RELAXED ASYNCHRONOUS ITERATIONS FOR THE LINEAR COMPLEMENTARITY PROBLEM

1. IntroductionConsider the large sparse Linear Complementarity Problem (LCP):where .1I = (mkj) 6 L(R") is a gitren real matrix and q = (qk) E R" a given real vector. Thisproblem arises in many areas of scientific computing. FOr example, it arises from problemsin (linear and) contrex quadratic programming, the prob1em of finding a Nash equilibriumpoint of a bimatrix game (e.g., Cottle and Dantzig[5] and Lemke[13]), a11d also a number of freeboundary problems of fluid mechanics (e.g., Cr…     

Asynchronous multisplitting methods for nonlinear fixed point problems

Our aim is to present for nonlinear problems asynchronous multisplitting algorithms including both the basic situation of O'Leary and White and the discrete analogue of Schwarz's alternating method and its multisubdomain extensions and moreover their two-stage counterparts. The analysis of these methods is based on El Tarazi’s convergence theorem for asynchronous iterations and leads to a good level of asynchronism in each of the considered situations. This revised version was published online in August 2006 with corrections to the Cover Date.     

广义异步矩阵多分裂向前向后松弛算法

本文建立了一类广义异步矩阵多分裂向前向后松弛算法，并在系数矩阵是Ｈ－矩阵的条件下，证明了这类算法的收敛性．     

异步并行矩阵多分裂块松弛迭代算法

1 引言 众所周知,许多微分方程经过差分或有限元离散,即可归结为线性代数方程组 Ax=b,A∈L(R~n)非奇异,x,b∈R~n.(1.1)缘于原问题的物理特性,系数矩阵A∈L(R~n)通常是大型稀疏的,并且具有规则的分块结构。鉴此,文[1]基于矩阵多重分裂的概念,并运用线性迭代法的松弛加速技巧,提出了求解这类大型稀疏分块线性代数方程组的并行矩阵多分裂块松弛迭代算法,并在适当的条件下建立了算法的收敛理论。对于SIMD多处理机系统,这类算法是颇为适用和行之有效的。     

Multisplitting Iteration Schemes for Solving a Class of Nonlinear Complementarity Problems

We consider several synchronous and asynchronous multisplitting iteration schemes for solving aclass of nonlinear complementarity problems with the system matrix being an H-matrix.We establish theconvergence theorems for the schemes.The numerical experiments show that the schemes are efficient forsolving the class of nonlinear complementarity problems.