Rational Krylov for Nonlinear Eigenproblems,an Iterative Projection Method

In recent papers Ruhe suggested a rational Krylov method for nonlinear eigenproblems knitting together a secant method for linearizing the nonlinear problem and the Krylov method for the linearized problem. In this note we point out that the method can be understood as an iterative projection method. Similarly to the Arnoldi method the search space is expanded by the direction from residual inverse iteration. Numerical methods demonstrate that the rational Krylov method can be accelerated considerably by replacing an inner iteration by an explicit solver of projected problems.     

The Impact of Equal Weighting of Low- and High-Confidence Observations on Robust Linear Regression Computations

Equal weighting of low- and high-confidence observations occurs for Huber, Talwar, and Barya weighting functions when Newton's method is used to solve robust linear regression problems. This leads to easy updates and/or downdates of existing matrix factorizations or easy computation of coefficient matrices in linear systems from previous ones. Thus Newton's method based on these functions has been shown to be computationally cheap. In this paper we show that a combination of Newton's method and an iterative method is a promising approach for solving robust linear regression problems. We show that Newton's method based on the Talwar function is an active set method. Further we show that it is possible to obtain improved estimates of the solution vector by combining a line search method like Newton's method with an active set method.This revised version was published online in October 2005 with corrections to the Cover Date.     

On diagonally structured problems in unconstrained optimization using an inexact super Halley method

We consider solving the unconstrained minimization problem using an iterative method derived from the third order super Halley method. Each iteration of the super Halley method requires the solution of two linear systems of equations. We show a practical implementation using an iterative method to solve the linear systems. This paper introduces an array of arrays (jagged) data structure for storing the second and third derivative of a multivariate function and suitable termination criteria for the (inner) iterative method to achieve a cubic rate of convergence. Using a jagged compressed diagonal storage of the Hessian matrices and for the tensor, numerical results show that storing the diagonals are more efficient than the row or column oriented approach when we use an iterative method for solving the linear systems of equations.     

Identification of a time-dependent source term for a time fractional diffusion problem

In this paper, we study an inverse problem of identifying a time-dependent term of an unknown source for a time fractional diffusion equation using nonlocal measurement data. Firstly, we establish the conditional stability for this inverse problem. Then two regularization methods are proposed to for reconstructing the time-dependent source term from noisy measurements. The first method is an integral equation method which formulates the inverse source problem into an integral equation of the second kind; and a prior convergence rate of regularized solutions is derived with a suitable choice strategy of regularization parameters. The second method is a standard Tikhonov regularization method and formulates the inverse source problem as a minimizing problem of the Tikhonov functional. Based on the superposition principle and the technique of finite-element interpolation, a numerical scheme is proposed to implement the second regularization method. One- and two-dimensional examples are carried out to verify efficiency and stability of the second regularization method.     

Long-Time Oscillatory Energy Conservation of Total Energy-Preserving Methods for Highly Oscillatory Hamiltonian Systems

For an integrator when applied to a highly oscillatory system,the near conservation of the oscillatory energy over long times is an important aspect.In this paper,we study the long-time near conservation of oscillatory energy for the adapted average vector field(AAVF)method when applied to highly oscillatory Hamiltonian systems.This AAVF method is an extension of the average vector field method and preserves the total energy of highly oscillatory Hamiltonian systems exactly.This paper is devoted to analysing another important property of AAVF method,i.e.,the near conservation of its oscillatory energy in a long term.The long-time oscillatory energy conservation is obtained via constructing a modulated Fourier expansion of the AAVF method and deriving an almost invariant of the expansion.A similar result of the method in the multi-frequency case is also presented in this paper.     

A method based on Rayleigh quotient gradient flow for extreme and interior eigenvalue problems

Recently, a continuous method has been proposed by Golub and Liao as an alternative way to solve the minimum and interior eigenvalue problems. According to their numerical results, their method seems promising. This article is an extension along this line. In this article, firstly, we convert an eigenvalue problem to an equivalent constrained optimization problem. Secondly, using the Karush-Kuhn-Tucker conditions of this equivalent optimization problem, we obtain a variant of the Rayleigh quotient gradient flow, which is formulated by a system of differential-algebraic equations. Thirdly, based on the Rayleigh quotient gradient flow, we give a practical numerical method for the minimum and interior eigenvalue problems. Finally, we also give some numerical experiments of our method, the Golub and Liao method, and EIGS (a Matlab implementation for computing eigenvalues using restarted Arnoldi’s method) for some typical eigenvalue problems. Our numerical experiments indicate that our method seems promising for most test problems.     

A Hybrid Algorithm for the Non-Guillotine Cutting Problem

In this article, a meta-heuristic method to solve the non-guillotine cutting stock problem is proposed. The method is based on a combination between the basic principles of the constructive and evolutive methods. With an adequate management of the parameters involved, the method allows regulation of the solution quality to computational effort relationship. This method is applied to a particular case of cutting problems, with which the computational behaviors is evaluated. In fact, 1000 instances of the problem have been classified according to their combinatorial degree and then the efficiency and robustness of the method have been tested. The final results conclude that the proposed method generates an average error close to 2.18% with respect to optimal solutions. It has also been verified that the method yields solutions for all of the instances examined; something that has not been achieved with an exact constructive method, which was also implemented. Comparison of the running times demonstrates the superiority of the proposed method as compared with the exact method.     

An operator splitting strategy for fluid–structure interaction problems with thin elastic structures in an incompressible Newtonian flow

We present a computational framework based on the use of the Newton and level set methods to model fluid–structure interaction problems involving elastic membranes freely suspended in an incompressible Newtonian flow. The Mooney–Rivlin constitutive model is used to model the structure. We consider an extension to a more general case of the method described in Laadhari (2017) to model the elasticity of the membrane. We develop a predictor–corrector finite element method where an operator splitting scheme separates different physical phenomena. The method features an affordable computational burden with respect to the fully implicit methods. An exact Newton method is described to solve the problem, and the quadratic convergence is numerically achieved. Sample numerical examples are reported and illustrate the accuracy and robustness of the method.     

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。     

A goal programming method for obtaining interval weights from an interval comparison matrix

Crisp comparison matrices lead to crisp weight vectors being generated. Accordingly, an interval comparison matrix should give an interval weight estimate. In this paper, a goal programming (GP) method is proposed to obtain interval weights from an interval comparison matrix, which can be either consistent or inconsistent. The interval weights are assumed to be normalized and can be derived from a GP model at a time. The proposed GP method is also applicable to crisp comparison matrices. Comparisons with an interval regression analysis method are also made. Three numerical examples including a multiple criteria decision-making (MCDM) problem with a hierarchical structure are examined to show the potential applications of the proposed GP method.     

多源异构数据环境下基于模糊积分融合的公租房退出方法

为有效解决公租房退出问题,提出一种基于多源异构数据的模糊积分融合退出方法,该退出方法首先给出一种多源异构数据的同构化方法,然后针对常用模糊测度确定方法原理复杂、计算困难的问题,提出一种原理简单、易于计算的模糊测度确定方法,该模糊测度确定方法利用单个属性的相对重要程度和两两属性之间的交互度计算单个属性的全局重要程度,最后,根据模糊测度的单调性和有界性通过专家逐级打分计算各子属性集的重要程度。实例验证表明所提出的退出方法可行、有效。     

Exponential meshes and three‐dimensional computation of a magnetic field

We describe the simulation of an exterior problem using a magnetic field deriving from magnetostatics, with a numerical method mixing the approaches of C. I. Goldstein and L.‐A. Ying. This method is based on the use of a graded mesh obtained by gluing homothetic layers in the exterior domain. On this mesh, we use an edge elements discretization and a recently proposed mixed formulation. In this paper, we provide both a theoretical and numerical study of the method. We establish an error estimate, describe the implementation, propose some preconditioning techniques and show the numerical results. We also compare these results with those obtained from an equivalent boundary elements approach. In this way, we retain that our method leads to a practical numerical implementation, a saving of storage, and turns out to be an alternative to the classical boundary elements method. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 19: 595–637, 2003     

Partial regularization method for nonmonotone variational inequalities

A variational inequality with a nonmonotone mapping is considered in a Euclidean space. A regularization method with respect to some of the variables is proposed for its solution. The convergence of the method is proved under a coercivity-type condition. The method is applied to an implicit optimization problem with an arbitrary perturbing mapping. The solution technique combines partial regularization and the dual descent method.     

An efficient gradient method with approximate optimal stepsize for the strictly convex quadratic minimization problem

In this paper, a new type of stepsize, approximate optimal stepsize, for gradient method is introduced to interpret the Barzilai–Borwein (BB) method, and an efficient gradient method with an approximate optimal stepsize for the strictly convex quadratic minimization problem is presented. Based on a multi-step quasi-Newton condition, we construct a new quadratic approximation model to generate an approximate optimal stepsize. We then use the two well-known BB stepsizes to truncate it for improving numerical effects and treat the resulted approximate optimal stepsize as the new stepsize for gradient method. We establish the global convergence and R-linear convergence of the proposed method. Numerical results show that the proposed method outperforms some well-known gradient methods.     

On the Convergence of the Brent Method

1.IntroductionItiswellknownthattheBrentmethodforsolvingsystemsofnonlinearequati0nsistosolvethefo1lowingsystem:bymaldnguseoftheorthogonaltriangulaxfaCtoriz8tion.SupP0sethatwehaveanaPprokimationx(k)tox*,asoluti0nof(1.1).Thenthek-thiterativeprocedurecanbedescribedasfollows[1]:wherehk/Oisthedifferencestepcorrespondingtotheindexk(wewilldiscussthechoicesofhkinSecti0n4)-Constructanorthogonalmatrix(usuallybytheHouseholdtransf0rmation)Step4.Ifj相似文献   

Interactive Compromise Programming

The purpose of this paper is to introduce a solution method for multiple objective linear programming (MOLP) problems. The method, called interactive compromise programming (ICP), offers a practical solution to MOLP problems by combining judgement with an automatic optimization technique in decision-making. This is realised by using the method of compromise programming and the method of a two-person zero-sum game in an iterative way. The method is illustrated by a numerical example.     

自由边界问题的自适应Uzawa块松弛算法

利用增广Lagrange乘子法和自适应法则，得到求解单侧障碍自由边界问题的自适应Uzawa块松弛法.单侧障碍自由边界问题离散为有限维线性互补问题，等价于一个用辅助变量和增广Lagrange函数表示的鞍点问题.采用Uzawa块松弛算法求解该问题得到一个两步迭代法，主要的子问题为一个线性问题，同时能显式求解辅助变量.由于Uzawa块松弛算法的收敛速度显著依赖于罚参数，而且对具体问题很难选择合适的罚参数.为提高算法的性能，提出了自适应法则，该方法自动调整每次迭代所需的罚参数.数值结果验证了该算法的理论分析.     

Derivative-Free Filter Simulated Annealing Method for Constrained Continuous Global Optimization

In this paper, a simulated-annealing-based method called Filter Simulated Annealing (FSA) method is proposed to deal with the constrained global optimization problem. The considered problem is reformulated so as to take the form of optimizing two functions, the objective function and the constraint violation function. Then, the FSA method is applied to solve the reformulated problem. The FSA method invokes a multi-start diversification scheme in order to achieve an efficient exploration process. To deal with the considered problem, a filter-set-based procedure is built in the FSA structure. Finally, an intensification scheme is applied as a final stage of the proposed method in order to overcome the slow convergence of SA-based methods. The computational results obtained by the FSA method are promising and show a superior performance of the proposed method, which is a point-to-point method, against population-based methods.     

开关函数的一个极小化方法

<正> 在组合电路的逻辑设计中,经常遇到用二级与-或网络实现任意给定的开关函数的问题.开关函数的极小化方法就是研究如何得到一个既经济又简单的网络来实现任意给定的开关函数.目前已有的开关函数的极小化方法主要是制表法和交互积方法.本文的目的是将制表法和交互积方法结合起来,给出另一个极小化方法,同时给出这个方法的严格证明.     

凑合反推法和弹性理论中的多变量广义变分原理

详细介绍了如何应用凑合反推法(semi-inverse method)构造弹性理论中的两类独立变量的广义变分原理(包括熟知的Hellinger-Reissner变分原理,Hu-Washizu变分原理)及三类独立变量的广义变分原理(钱伟长广义变分原理) 。应用凑合反推法还可以清楚地看出各变量之间的约束关系,从而再一次证明了Hu-Washizu变分原理实际上是两类独立变量的广义变分原理。