Accelerated monotone iterative methods for finite difference equations of reaction-diffusion

This paper is concerned with numerical methods for a finite difference system of reaction-diffusion-convection equation under nonlinear boundary condition. Various monotone iterative methods are presented, and each of these methods leads to an existence-comparison theorem as well as a computational algorithm for numerical solutions. The monotone property of the iterations gives improved upper and lower bounds of the solution in each iteration, and the rate of convergence of the iterations is either quadratic or nearly quadratic depending on the property of the nonlinear function. Application is given to a model problem from chemical engineering, and some numerical results, including a test problem with known analytical solution, are presented to illustrate the various rates of convergence of the iterations. Received November 2, 1995 / Revised version received February 10, 1997     

Z-矩阵的预条件方法

通过对方程组Ax=b的系数矩阵施行初等行变换，该文提出了解线性方程组Ax=b的一种新的预条件Gauss Seidel迭代方法，理论上证明了新的预条件Gauss Seidel迭代方法较经典的Gauss Seidel迭代法收敛速度快. 该文提出的新预条件方法推广了文［1-2］中提出的预条件方法，具体的数值例子说明了新预条件方法的有效性.     

Accelerated iterative methods for finding solutions of a system of nonlinear equations

In this paper, we present a technique to construct iterative methods to approximate the zeros of a nonlinear equation F(x)=0, where F is a function of several variables. This technique is based on the approximation of the inverse function of F and on the use of a fixed point iteration. Depending on the number of steps considered in the fixed point iteration, or in other words, the number of evaluations of the function F, we obtain some variants of classical iterative processes to solve nonlinear equations. These variants improve the order of convergence of classical methods. Finally, we show some numerical examples, where we use adaptive multi-precision arithmetic in the computation that show a smaller cost.     

一类Z-矩阵的置换结构

利用图论方法并结合Z－矩阵的本身特点，讨论了对角元全为零的Z－矩阵的伴随有向图性质，并由给出了对角元全为零的非奇异Z－矩阵的置换结构。     

Hidden Z-matrices with positive principal minors

Let $\text{C}$ denote the class of hidden Z-matrices, i.e., $\text{M∈}\text{C}$ if and only if there exist Z-matrices X and Y such that the following two conditions are satisfied:

$\text{(}\text{M}\text{1) MX = Y,}$

$\text{(}\text{M}\text{2) r}{}^{\mathrm{T}}\text{X + s}{}^{\mathrm{T}}\text{Y > 0}\text{for some}\text{r, s ? 0.}$

Let P denote the class of real square matrices having positive principal minors. The class $\text{C}$ has arisen recently as a generalization of the class of Z-matrices [9,23,24]. In this paper, we explore various matrix-theoretic aspects of the class $\text{C}\text{∩P}$.     

An iterative method for solving nonlinear equations

An iterative method for finding a solution of the equation f(x)=0$f(x)=0$ is presented. The method is based on some specially derived quadrature rules. It is shown that the method can give better results than the Newton method.     

On an iterative method for variational inequalities

Summary A number of numerical solutions are presented as examples of a new iterative method for variational inequalities. The iterative method is based on the reduction of variational inequalities to the Wiener-Hopf equations. For obstacle problems the convergence is guaranteed inW ^1,p spaces forp2. The examples presented are one and two dimensional obstacle problems in cases when the Greens function is known, but the method is very general.     

Modified Householder iterative method for nonlinear equations

In this paper, we suggest and analyze a new two-step predictor–corrector type iterative method for solving nonlinear equations of the type f(x)=0. This new method includes the two-step Newton method as a special case. We show that this new two-step method is a sixth-order convergent method. Several examples are given to illustrate the efficiency of this new method and its comparison with other sixth-order methods. This method can be considered as a significant improvement of the Newton method and its variant forms.     

An iterative method for solving semismooth equations

In this paper, we combine trust region technique with line search technique to develop an iterative method for solving semismooth equations. At each iteration, a trust region subproblem is solved. The solution of the trust region subproblem provides a descent direction for the norm of a smoothing function. By using a backtracking line search, a steplength is determined. The proposed method shares advantages of trust region methods and line search methods. Under appropriate conditions, the proposed method is proved to be globally and superlinearly convergent. In particular, we show that after finitely many iterations, the unit step is always accepted and the method reduces to a smoothing Newton method.     

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     

An iterative method for ill-posed problems with inequalities

Ill-posed problems for integral and operator equations with nonnegativity and band inequality constraints arise in a wide range of applications. The effect and propagation of data perturbations in mathematical programming problems are highly dramatized in the area of ill-posed problems. In this note an iterative method for solving an ill-posed integral inequality and its moment discretization is described.     

A modified SSOR iterative method for augmented systems

Golub, Wu and Yuan [G.H. Golub, X. Wu, J.Y. Yuan, SOR-like methods for augmented systems, BIT 41 (2001) 71–85] have presented the SOR-like algorithm to solve augmented systems. In this paper, we present the modified symmetric successive overrelaxation (MSSOR) method for solving augmented systems, which is based on Darvishi and Hessari’s work above. We derive its convergence under suitable restrictions on the iteration parameter, determine its optimal iteration parameter and the corresponding optimal convergence factor under certain conditions. Finally, we apply the MSSOR method to solve augmented systems.     

A new iterative method for discrete HJB equations

A successive relaxation iterative algorithm for discrete HJB equations is proposed. Monotone convergence has been proved for the algorithm. This work was supported by NNSF of China (no. 10571046).