GLOBAL CONVERGENCE AND IMPLEMENTATION OF NGTN METHOD FOR SOWING LARGE-SCALE SMRSE NONLINEAR PROGRAMMING PROBLEMS

1. IntroductionConsider the following NLP problemwhere the function f: Re --+ RI and gi: Re - R', j E J are twice continuously dtherentiable.In particular, we discuss the cajse, where the nUmber of variables and the nUmber of constraintsin (1.1) are large and second derivatives in (1.1) are sparse.There are some methods whiCh can solve largesscale problems, e.g. Lancelot in [2] andTDSQPLM in [9]. But they can not take adVantage of sparse structtire of the problem. A newefficient meth…     

An alternating direction Galerkin method for elliptic problems with gradient nonlinearity

Several problems in many applications involve the solution of partial differential equations with gradient dependent nonlinearity. The numerical solution of the resulting nonlinear system is rather expensive. We present an alternating direction Galerkin method that allows much faster solution of the nonlinear system. The alternating direction formulation help reduce the problem into a sequence of nonlinear systems that may be solved very efficiently. Theoretical study of the convergence of the method will also be presented. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

一类改进的非凸二次规划有效集方法

一类改进的非凸二次规划有效集方法修乃华（河北师范学院数学系）ＡＣＬＡＳＳＯＦＩＭＰＲＯＶＥＤＡＣＴＩＶＥＳＥＴＭＥＴＨＯＤＳＦＯＲＮＯＮＣＯＮＶＥＸＱＵＡＤＲＡＴＩＣＰＲＯＧＲＡＭＭＩＮＧＰＲＯＢＬＥＭ￥ＸｉｕＮａｉ－ｈｕａ（Ｄｅｐｔ．ｏｆＭａｔｈ．...     

A two-stage feasible directions algorithm for nonlinear constrained optimization

We present a feasible directions algorithm, based on Lagrangian concepts, for the solution of the nonlinear programming problem with equality and inequality constraints. At each iteration a descent direction is defined; by modifying it, we obtain a feasible descent direction. The line search procedure assures the global convergence of the method and the feasibility of all the iterates. We prove the global convergence of the algorithm and apply it to the solution of some test problems. Although the present version of the algorithm does not include any second-order information, like quasi-Newton methods, these numerical results exhibit a behavior comparable to that of the best methods known at present for nonlinear programming. Research performed while the author was on a two years appointment at INRIA, Rocquencourt, France, and partially supported by the Brazilian Research Council (CNPq).     

A higher order uniformly convergent method for singularly perturbed parabolic turning point problems

In this article, we study numerical approximation for a class of singularly perturbed parabolic (SPP) convection-diffusion turning point problems. The considered SPP problem exhibits a parabolic boundary layer in the neighborhood of one of the sides of the domain. Some a priori bounds are given on the exact solution and its derivatives, which are necessary for the error analysis. A numerical scheme comprising of implicit finite difference method for time discretization on a uniform mesh and a hybrid scheme for spatial discretization on a generalized Shishkin mesh is proposed. Then Richardson extrapolation method is applied to increase the order of convergence in time direction. The resulting scheme has second-order convergence up to a logarithmic factor in space and second-order convergence in time. Numerical experiments are conducted to demonstrate the theoretical results and the comparative study is done with the existing schemes in literature to show better accuracy of the proposed schemes.     

A parameter-free multiplier method for constrained minimization problems

This paper is concerned with the development of a parameter-free method, closely related to penalty function and multiplier methods, for solving constrained minimization problems. The method is developed via the quadratic programming model with equality constraints. The study starts with an investigation into the convergence properties of a so-called “primal-dual differential trajectory”, defined by directions given by the direction of steepest descent with respect to the variables x of the problem, and the direction of steepest ascent with respect to the Lagrangian multipliers λ, associated with the Lagrangian function. It is shown that the trajectory converges to a stationary point (x*, λ*) corresponding to the solution of the equality constrained problem. Subsequently numerical procedures are proposed by means of which practical trajectories may be computed and the convergence of these trajectories are analyzed. A computational algorithm is presented and its application is illustrated by means of simple but representative examples. The extension of the method to inequality constrained problems is discussed and a non-rigorous argument, based on the Kuhn—Tucker necessary conditions for a constrained minimum, is put forward on which a practical procedure for determining the solution is based. The application of the method to inequality constrained problems is illustrated by its application to a couple of simple problems.     

A higher order difference method for singularly perturbed parabolic partial differential equations

This paper studies a higher order numerical method for the singularly perturbed parabolic convection-diffusion problems where the diffusion term is multiplied by a small perturbation parameter. In general, the solutions of these type of problems have a boundary layer. Here, we generate a spatial adaptive mesh based on the equidistribution of a positive monitor function. Implicit Euler method is used to discretize the time variable and an upwind scheme is considered in space direction. A higher order convergent solution with respect to space and time is obtained using the postprocessing based extrapolation approach. It is observed that the convergence is independent of perturbation parameter. This technique enhances the order of accuracy from first order uniform convergence to second order uniform convergence in space as well as in time. Comparative study with the existed meshes show the highly effective behavior of the present method.     

Strongly sub-feasible direction method for constrained optimization problems with nonsmooth objective functions

In this paper, we propose a strongly sub-feasible direction method for the solution of inequality constrained optimization problems whose objective functions are not necessarily differentiable. The algorithm combines the subgradient aggregation technique with the ideas of generalized cutting plane method and of strongly sub-feasible direction method, and as results a new search direction finding subproblem and a new line search strategy are presented. The algorithm can not only accept infeasible starting points but also preserve the “strong sub-feasibility” of the current iteration without unduly increasing the objective value. Moreover, once a feasible iterate occurs, it becomes automatically a feasible descent algorithm. Global convergence is proved, and some preliminary numerical results show that the proposed algorithm is efficient.     

A parameter‐uniform scheme for the parabolic singularly perturbed problem with a delay in time

In this paper, a parameter‐uniform numerical scheme for the solution of singularly perturbed parabolic convection–diffusion problems with a delay in time defined on a rectangular domain is suggested. The presence of the small diffusion parameter ? leads to a parabolic right boundary layer. A collocation method consisting of cubic B ‐spline basis functions on an appropriate piecewise‐uniform mesh is used to discretize the system of ordinary differential equations obtained by using Rothe's method on an equidistant mesh in the temporal direction. The parameter‐uniform convergence of the method is shown by establishing the theoretical error bounds. The numerical results of the test problems validate the theoretical error bounds.     

随机ADMM算法及其在电力系统凸经济调度问题中的应用

针对电力系统中的一类凸经济调度问题,提出了随机ADMM算法,设计了周期循环更新规则和随机选择更新规则,证明了随机ADMM算法在周期循环更新规则下的收敛性,以及得出了在随机选择更新规则下按期望收敛的结论.数值实验结果表明该方法可以有效解决电力系统中的凸经济调度问题.     

修正PRP共轭梯度方法求解无约束最优化问题

基于著名的PRP共轭梯度方法,利用CG_DESCENT共轭梯度方法的结构,本文提出了一种求解大规模无约束最优化问题的修正PRP共轭梯度方法。该方法在每一步迭代中均能够产生一个充分下降的搜索方向,且独立于任何线搜索条件。在标准Wolfe线搜索条件下,证明了修正PRP共轭梯度方法的全局收敛性和线性收敛速度。数值结果展示了修正PRP方法对给定的测试问题是非常有效的。     

修正PRP共轭梯度方法求解无约束最优化问题

基于著名的PRP共轭梯度方法,利用CG_DESCENT共轭梯度方法的结构,本文提出了一种求解大规模无约束最优化问题的修正PRP共轭梯度方法。该方法在每一步迭代中均能够产生一个充分下降的搜索方向,且独立于任何线搜索条件。在标准Wolfe线搜索条件下,证明了修正PRP共轭梯度方法的全局收敛性和线性收敛速度。数值结果展示了修正PRP方法对给定的测试问题是非常有效的。     

A stochastic collocation method for the second order wave equation with a discontinuous random speed

In this paper we propose and analyze a stochastic collocation method for solving the second order wave equation with a random wave speed and subjected to deterministic boundary and initial conditions. The speed is piecewise smooth in the physical space and depends on a finite number of random variables. The numerical scheme consists of a finite difference or finite element method in the physical space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space. This approach leads to the solution of uncoupled deterministic problems as in the Monte Carlo method. We consider both full and sparse tensor product spaces of orthogonal polynomials. We provide a rigorous convergence analysis and demonstrate different types of convergence of the probability error with respect to the number of collocation points for full and sparse tensor product spaces and under some regularity assumptions on the data. In particular, we show that, unlike in elliptic and parabolic problems, the solution to hyperbolic problems is not in general analytic with respect to the random variables. Therefore, the rate of convergence may only be algebraic. An exponential/fast rate of convergence is still possible for some quantities of interest and for the wave solution with particular types of data. We present numerical examples, which confirm the analysis and show that the collocation method is a valid alternative to the more traditional Monte Carlo method for this class of problems.     

A Truncated Nonmonotone Gauss-Newton Method for Large-Scale Nonlinear Least-Squares Problems

In this paper, a Gauss-Newton method is proposed for the solution of large-scale nonlinear least-squares problems, by introducing a truncation strategy in the method presented in [9]. First, sufficient conditions are established for ensuring the convergence of an iterative method employing a truncation scheme for computing the search direction, as approximate solution of a Gauss-Newton type equation. Then, a specific truncated Gauss-Newton algorithm is described, whose global convergence is ensured under standard assumptions, together with the superlinear convergence rate in the zero-residual case. The results of a computational experimentation on a set of standard test problems are reported.     

A preconditioned descent algorithm for variational inequalities of the second kind involving the <Emphasis Type="Italic">p</Emphasis>-Laplacian operator

This paper is concerned with the numerical solution of a class of variational inequalities of the second kind, involving the p-Laplacian operator. This kind of problems arise, for instance, in the mathematical modelling of non-Newtonian fluids. We study these problems by using a regularization approach, based on a Huber smoothing process. Well posedness of the regularized problems is proved, and convergence of the regularized solutions to the solution of the original problem is verified. We propose a preconditioned descent method for the numerical solution of these problems and analyze the convergence of this method in function spaces. The existence of admissible descent directions is established by variational methods and admissible steps are obtained by a backtracking algorithm which approximates the objective functional by polynomial models. Finally, several numerical experiments are carried out to show the efficiency of the methodology here introduced.     

Continuous-discontinuous finite element method for convection-diffusion problems with characteristic layers

We study convergence properties of a numerical method for convection-diffusion problems with characteristic layers on a layer-adapted mesh. The method couples standard Galerkin with an h-version of the nonsymmetric discontinuous Galerkin finite element method with bilinear elements. In an associated norm, we derive the error estimate as well as the supercloseness result that are uniform in the perturbation parameter. Applying a post-processing operator for the discontinuous Galerkin method, we construct a new numerical solution with enhanced convergence properties.     

A new class of hybrid extragradient algorithms for solving quasi-equilibrium problems

Generalized Nash equilibrium problems are important examples of quasi-equilibrium problems. The aim of this paper is to study a general class of algorithms for solving such problems. The method is a hybrid extragradient method whose second step consists in finding a descent direction for the distance function to the solution set. This is done thanks to a linesearch. Two descent directions are studied and for each one several steplengths are proposed to obtain the next iterate. A general convergence theorem applicable to each algorithm of the class is presented. It is obtained under weak assumptions: the pseudomonotonicity of the equilibrium function and the continuity of the multivalued mapping defining the constraint set of the quasi-equilibrium problem. Finally some preliminary numerical results are displayed to show the behavior of each algorithm of the class on generalized Nash equilibrium problems.     

解可分离结构变分不等式的一种新的交替方向法

交替方向法是求解可分离结构变分不等式问题的经典方法之一, 它将一个大型的变分不等式问题分解成若干个小规模的变分不等式问题进行迭代求解. 但每步迭代过程中求解的子问题仍然摆脱不了求解变分不等式子问题的瓶颈. 从数值计算上来说, 求解一个变分不等式并不是一件容易的事情.因此, 本文提出一种新的交替方向法, 每步迭代只需要求解一个变分不等式子问题和一个强单调的非线性方程组子问题. 相对变分不等式问题而言, 我们更容易、且有更多的有效算法求解一个非线性方程组问题. 在与经典的交替方向法相同的假设条件下, 我们证明了新算法的全局收敛性. 进一步的数值试验也验证了新算法的有效性.     

Convergence and stability of a numerical method for micromagnetics

The convergence and stability of a numerical method, which applies a nonconforming finite element method and an artificial boundary method to a multi-atomic Young measure relaxation model, for micromagnetics are analyzed. By revealing some key properties of the solution sets of both the continuous and discrete problems, we show that our numerical method is stable, and the solution set of the continuous problem is well approximated by those of the discrete problems. The performance of our method is also illustrated by some numerical examples. The research was supported in part by the Major State Basic Research Projects (2005CB321701), NSFC projects (10431050, 10571006, 10528102 and 10871011) and RFDP of China.     

B-spline collocation for solution of two-point boundary value problems

A numerical method based on B-spline is developed to solve the general nonlinear two-point boundary value problems up to order 6. The standard formulation of sextic spline for the solution of boundary value problems leads to non-optimal approximations. In order to derive higher orders of accuracy, high order perturbations of the problem are generated and applied to construct the numerical algorithm. The error analysis and convergence properties of the method are studied via Green’s function approach. O(h⁶) global error estimates are obtained for numerical solution of these classes of problems. Numerical results are given to illustrate the efficiency of the proposed method. Results of numerical experiments verify the theoretical behavior of the orders of convergence.