A Switching Algorithm Based on Modified Quasi-Newton Equation

In this paper, a switching method for unconstrained minimization is proposed. The method is based on the modified BFGS method and the modified SR1 method. The eigenvalues and condition numbers of both the modified updates are evaluated and used in the switching rule. When the condition number of the modified SR1 update is superior to the modified BFGS update, the step in the proposed quasi-Newton method is the modified SR1 step. Otherwise the step is the modified BFGS step. The efficiency of the proposed method is tested by numerical experiments on small, medium and large scale optimization. The numerical results are reported and analyzed to show the superiority of the proposed method.     

GL method for solving equations in math-physics and engineering

In this paper, we propose a GL method for solving the ordinary and the partial differential equation in mathematical physics and chemics and engineering. These equations govern the acustic, heat, electromagnetic, elastic, plastic, flow, and quantum etc. macro and micro wave field in time domain and frequency domain. The space domain of the differential equation is infinite domain which includes a finite inhomogeneous domain. The inhomogeneous domain is divided into finite sub domains. We present the solution of the differential equation as an explicit recursive sum of the integrals in the inhomogeneous sub domains. Actualy, we propose an explicit representation of the inhomogeneous parameter nonlinear inversion. The analytical solution of the equation in the infinite homogeneous domain is called as an initial global field. The global field is updated by local scattering field successively subdomaln by subdomain. Once all subdomains are scattered and the updating process is finished in all the sub domains, the solution of the equation is obtained. We call our method as Global and Local field method, in short , GL method. It is different from FEM method, the GL method directly assemble inverse matrix and gets solution. There is no big matrix equation needs to solve in the GL method. There is no needed artificial boundary and no absorption boundary condition for infinite domain in the GL method. We proved several theorems on relationships between the field solution and Green＇s function that is the theoretical base of our GL method. The numerical discretization of the GL method is presented. We proved that the numerical solution of the GL method convergence to the exact solution when the size of the sub domain is going to zero. The error estimation of the GL method for solving wave equation is presented. The simulations show that the GL method is accurate, fast, and stable for solving elliptic, parabolic, and hyperbolic equations. The GL method has advantages and wide applications in the 3D electromagnetic （EM）     

解变分不等式问题的混合方法

By using Fukushima‘s differentiable merit function,Taji,Fukushima and Ibaraki have given a globally convergent modified Newton method for the strongly monotone variational inequality problem and proved their method to be quadratically convergent under certain assumptions in 1993. In this paper a hybrid method for the variational inequality problem under the assumptions that the mapping F is continuously differentiable and its Jacobian matrix F(x) is positive definite for all x∈S rather than strongly monotone and that the set S is nonempty, polyhedral,closed and convex is proposed. Armijo-type line search and trust region strategies as well as Fukushima‘s differentiable merit function are incorporated into the method. It is then shown that the method is well defined and globally convergent and that,under the same assumptions as those of Taji et al. ,the method reduces to the basic Newton method and hence the rate of convergence is quadratic. Computational experiences show the efficiency of the proposed method.     

A VARIATIONAL EXPECTATION-MAXIMIZATION METHOD FOR THE INVERSE BLACK BODY RADIATION PROBLEM

The inverse black body radiation problem, which is to reconstruct the area temperature distribution from the measurement of power spectrum distribution, is a well-known ill-posed problem. In this paper, a variational expectation-maximization （EM） method is developed and its convergence is studied. Numerical experiments demonstrate that the variational EM method is more efficient and accurate than the traditional methods, including the Tikhonov regularization method, the Landweber method and the conjugate gradient method.     

对流扩散方程的三层UNO-MMOCAA差分方法

By combing the three-step modified method of characteristics and MMOCAA difference method with UNO interpolation, the three-step UNO-MMOCAA finite difference method is established for convection-dominated diffusion problems in this paper. The scheme is two-order accurate in space and time and is free from the oscillation near the steep front, with which the problem is solved by three-step MMOCAA finite difference method based on two-order Lagrange interplation. Using the new method, we give an estimate analysis of the scheme and a numerical example.     

A modified three–term conjugate gradient method with sufficient descent property

A hybridization of the three–term conjugate gradient method proposed by Zhang et al. and the nonlinear conjugate gradient method proposed by Polak and Ribi`ere, and Polyak is suggested. Based on an eigenvalue analysis, it is shown that search directions of the proposed method satisfy the sufficient descent condition, independent of the line search and the objective function convexity. Global convergence of the method is established under an Armijo–type line search condition. Numerical experiments show practical efficiency of the proposed method.     

A METHOD FOR SOLVING THE INVERSE SCATTERING PROBLEM FOR SHAPE AND IMPEDANCE

The inverse problem considered in this paper is to determine the shape and the impedance of an obstacle from a knowledge of the time-harmonic incident field and the phase and amplitude of the far field pattern of the scattered wave in two-dimension. Single-layer potential is used to approach the scattered waves. An approximation method is presented and the convergence of the proposed method is established. Numerical examples are given to show that this method is both accurate and easy to use.     

A COLUMN-SECANT UPDATE TECHNIQUE FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

In this paper,we present a column-secant modification of the SCC method,which is called the CSSCC method.The CSSCC method uses function values more efficiently than the SCC method,and it is shown that the CSSCC method has better local q-convergence and r-convergence rates than the SCC method.The numerical results show that the CSSCC method is competitive with some well known methods for some standard test problems.     

A NEW NUMERICAL METHOD FOR TWO-PHASE IMMISCIBLE INCOMPRESSIBLE PROBLEM

Two-phase, immiscible, incompressible flow in porous media is governed by a system of nonlinear partial differential equations. In most practical applications convection physically dominates diffusion, and the object of this paper is to develop a finite difference method combined with the method of characteristics and the lumped mass method to treat the parabolic equation of the differential system. This method is shown satisfy the maximum principle and its error analysis is presented.     

A new trust region algorithm for image restoration

The image restoration problems play an important role in remote sensing and astronomical image analysis. One common method for the recovery of a true image from corrupted or blurred image is the least squares error (LSE) method. But the LSE method is unstable in practical applications. A popular way to overcome instability is the Tikhonov regularization. However, difficulties will encounter when adjusting the so-called regularization parameter a. Moreover, how to truncate the iteration at appropriate steps is also challenging. In this paper we use the trust region method to deal with the image restoration problem, meanwhile, the trust region subproblem is solved by the truncated Lanczos method and the preconditioned truncated Lanczos method. We also develop a fast algorithm for evaluating the Kronecker matrix-vector product when the matrix is banded. The trust region method is very stable and robust, and it has the nice property of updating the trust region automatically. This releases us from tedious fi     

自适应多重网格法与超松弛法的比较

多重网格法(Multiple Grid Method,简称M-G方法)是近年来出现的快速方法之一,本文在M-G方法中采用自适应控制层间转换的技术,并将自适应M-G方法与G-S迭代方法及SOR迭代方,法进行了比较。其计算结果表明,自适应M-G方法的计算量比G-S迭代及SOR迭代少得多,当M-G方法所用层数为4-6层,这种优越性就更加明显,且自适应M-G方法中选取控制参数有很大的灵活性。     

拟Raabe判别法与拟对数判别法的强弱关系

拟Raabe判别法是新近提出的关于正项级数收敛性的一种比较细致的判别法.对通项递减的正项级数来说,此判别法强于传统的Raabe判别法与Gauss判别法.通过对拟Raabe判别法与另一个细致的判别法——拟对数判别法强弱关系的探讨,得出了后一判别法强于前者的结论.     

一种求解非线性互补问题的方法及其收敛性

本文将Newton方法和外梯度方法相结合,提出了一种求解非线性互补问题的方法,证明了此方法的全局收敛性和超线性收敛性,在适当的条件下给出了一个有限终止结果。数值实验表明,此方法是有效的。     

A partial inexact alternating direction method for structured variational inequalities

In this article, a new method is proposed for solving a class of structured variational inequalities (SVIs). The proposed method is referred to as the partial inexact proximal alternating direction (piPAD) method. In the method, two subproblems are solved independently. One is handled by an inexact proximal point method and the other is solved directly. This feature is the major difference between the proposed method and some existing alternating direction-like methods. The convergence of the piPAD method is proved. Two examples of the modern convex optimization problem arising from engineering and information sciences, which can be reformulated into the encountered SVIs, are presented to demonstrate the applicability of the piPAD method. Also, some preliminary numerical results are reported to validate the feasibility and efficiency of the piPAD method.     

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.     

求解病态线性方程组的收缩Lanczos方法

Lanczos方法是求解大型线性方程组的常用方法.遗憾的是,在Lanczos过程中通常会发生算法中断或数值不稳定的情况.将给出求解大型对称线性方程组的收缩Lanczos方法,即DLanczos方法.新算法将采用增广子空间技术,在Lanczos过程中向Krylov子空间加入少量绝对值较小的特征值所对应的特征向量进行收缩.数值实验表明,新算法比Lanczos方法收敛速度更快,并且适合求解病态对称线性方程组.     

基于数值分布的激励型综合评价方法

针对激励评价中的等级划分问题,本文提出了一种基于数值分布的等级划分方法,相比于现有的等级划分方法,该方法能够综合考虑数值分布情况来划分等级,并结合本文提出的等级划分法对密度算子进行拓展,提出了一种基于数值分布的激励型综合评价方法。首先本文从数值分布的角度提出了一种新的等级划分方法,从而得出各等级区间的等级区间分界点;其次确定等级系数,并结合指标值和等级区间分界点给出各指标的权向量,给出一种不需要进行归一化处理的等级权向量确定方法,该方法能够较好的解决归一化处理带来的不公平性;再次根据密度算子思想对评价数据进行集结得出评价结果;最后通过一个算例对该方法进行验证,结果表明该方法可以实现对被评价对象科学激励的作用。该方法尤其适用于企业员工激励、省市综合排名、高校人才选拔等问题。     

基于蒙特卡洛仿真的理想点决策方法及其应用

首先分析了传统TOPS IS方法的基本原理和计算步骤,指出了传统TOPS IS方法应用时存在的限制与不足,提出了基于计算机蒙特卡洛仿真方法与传统理想点方法相结合的思想,该方法可以利用评测所给的区间值,既方便表述评测结果,也充分利用了评测结果,更加接近实际情况,因而,有助于提高决策质量.最后,通过复杂工程系统设计决策一个算例验证了该法的可行性与有效性.     

一个解凸二次规划的预测-校正光滑化方法

本文为凸二次规划问题提出一个光滑型方法,它是Engelke和Kanzow提出的解线性规划的光滑化算法的推广。其主要思想是将二次规划的最优性K-T条件写成一个非线性非光滑方程组,并利用Newton型方法来解其光滑近似。本文的方法是预测-校正方法。在较弱的条件下,证明了算法的全局收敛性和超线性收敛性。