一类新的具有充分下降条件和强收敛性的共轭梯度法（英文）

本文研究了求解无约束优化问题的WYL共轭梯度法.利用修正迭代格式,得到了算法在每步迭代能产生不依赖于搜索条件的充分下降方向.同时,在原算法中关于Wolfe条件中参数去掉的情况下,获得了本文算法是强收敛的.数值实验说明本文算法可以有效求解测试问题.     

对称线性互补问题的乘性Schwarz算法

本文提出了求解对称性互补问题的乘性Schwarz算法,其中子问题用投影迭代方法求解.利用投影迭代算子的性质及投影迭代的收敛性,证明了算法产生的迭代点列的聚点为原互补问题的解,并在一定条件下,证明算法产生的迭代点列的聚点存在.     

解无约束优化问题的一个新的带线搜索的信赖域算法

在传统信赖域方法的基础上, 提出了求解无约束最优化问题的一个新的带线搜索的信赖域算法. 该算法采用大步长 Armijo 线搜索技术获得迭代步长, 克服了每次迭代求解信赖域子问题时计算量较大的缺点, 因而适用于求解大型的优化问题. 在适当的条件下, 我们证明了算法的全局收敛性. 数值实验结果表明本文所提出的算法是有效的.     

等式约束优化非单调信赖域算法

设计了一个新的求解等式约束优化问题的非单调信赖域算法.该算法不需要罚函数也无需滤子.在每次迭代过程中只需求解满足下降条件的拟法向步及切向步.新算法产生的迭代步比滤子方法更易接受,计算量比单调算法小.在一般条件下,算法具有全局收敛性.     

约束优化无罚函数非单调SQP算法

本文研究求解非线性约束优化问题.利用非单调无罚函数方法,提出了一个新的序列二次规划算法.该算法在每次迭代过程中只需求解一个QP子问题和一个线性方程组.在一般条件下,算法具有全局收敛性,数值结果表明,计算量小于单调且含罚函数的传统算法.     

非线性极大极小问题一个新的QP-free算法

本文研究非线性无约束极大极小优化问题. QP-free算法是求解光滑约束优化问题的有效方法之一,但用于求解极大极小优化问题的成果甚少.基于原问题的稳定点条件,既不需含参数的指数型光滑化函数,也不要等价光滑化,提出了求解非线性极大极小问题一个新的QP-free算法.新算法在每一次迭代中,通过求解两个相同系数矩阵的线性方程组获得搜索方向.在合适的假设条件下,该算法具有全局收敛性.最后,初步的数值试验验证了算法的有效性.     

凸约束伪单调方程组的无导数投影算法

基于HS共轭梯度法的结构,本文在弱假设条件下建立了一种求解凸约束伪单调方程组问题的迭代投影算法.该算法不需要利用方程组的任何梯度或Jacobian矩阵信息,因此它适合求解大规模问题.算法在每一次迭代中都能产生充分下降方向,且不依赖于任何线搜索条件.特别是,我们在不需要假设方程组满足Lipschitz条件下建立了算法的全局收敛性和R-线收敛速度.数值结果表明,该算法对于给定的大规模方程组问题是稳定和有效的.     

一类线性约束矩阵不等式及其最小二乘问题

本文主要考虑一类线性矩阵不等式及其最小二乘问题,它等价于相应的矩阵不等式最小非负偏差问题.之前相关文献提出了求解该类最小非负偏差问题的迭代方法,但该方法在每步迭代过程中需要精确求解一个约束最小二乘子问题,因此对规模较大的问题,整个迭代过程需要耗费巨大的计算量.为了提高计算效率,本文在现有算法的基础上,提出了一类修正迭代方法.该方法在每步迭代过程中利用有限步的矩阵型LSQR方法求解一个低维矩阵Krylov子空间上的约束最小二乘子问题,降低了整个迭代所需的计算量.进一步运用投影定理以及相关的矩阵分析方法证明了该修正算法的收敛性,最后通过数值例子验证了本文的理论结果以及算法的有效性.     

凸二次半定规划一个新的原始对偶路径跟踪算法

本文提出求解凸二次半定规划的一个新的原始对偶路径跟踪算法.在每次迭代中,通过求解一个线性方程组产生搜索方向.在一定条件下证明算法产生的迭代点列落在中心路径的邻域内,且算法至多经■次迭代可得到一个ε-最优解.     

MBFGS算法中迭代矩阵的收敛性

Li-Fukushima[3]提出了一种修正的BFGS方法MBFGS算法.本文研究MBFGS算法中迭代矩阵的收敛性.我们证明在一定条件下,MBFGS算法用于求解严格凸二次函数极小值时产生的迭代矩阵序列是收敛的.     

Global optimality conditions and optimization methods for quadratic integer programming problems

In this paper, we first establish some sufficient and some necessary global optimality conditions for quadratic integer programming problems. Then we present a new local optimization method for quadratic integer programming problems according to its necessary global optimality conditions. A new global optimization method is proposed by combining its sufficient global optimality conditions, local optimization method and an auxiliary function. The numerical examples are also presented to show that the proposed optimization methods for quadratic integer programming problems are very efficient and stable.     

An augmented Lagrangian proximal alternating method for sparse discrete optimization problems

In this paper, we propose an augmented Lagrangian proximal alternating (ALPA) method for solving two classes of large-scale sparse discrete constrained optimization problems. Specifically, the ALPA method generates a sequence of augmented Lagrangian (AL) subproblems in the out iterations and utilizes a proximal alternating linearized minimization method and sparse projection techniques to solve these AL subproblems. And we study the first-order optimality conditions for these two classes of problems. Under some suitable assumptions, we show that any accumulation point of the sequence generated by the ALPA method satisfies the necessary first-order optimality conditions of these problems or is a local minimizer of these problems. The computational results with practical problems demonstrate that our method can find the suboptimal solutions of the problems efficiently and is competitive with some other local solution methods.

     

Some progress in spectral methods

In this paper,we review some results on the spectral methods.We frst consider the Jacobi spectral method and the generalized Jacobi spectral method for various problems,including degenerated and singular diferential equations.Then we present the generalized Jacobi quasi-orthogonal approximation and its applications to the spectral element methods for high order problems with mixed inhomogeneous boundary conditions.We also discuss the related spectral methods for non-rectangular domains and the irrational spectral methods for unbounded domains.Next,we consider the Hermite spectral method and the generalized Hermite spectral method with their applications.Finally,we consider the Laguerre spectral method and the generalized Laguerre spectral method for many problems defned on unbounded domains.We also present the generalized Laguerre quasi-orthogonal approximation and its applications to certain problems of non-standard type and exterior problems.     

Solution blowup for systems of shallow-water equations

We consider initial-boundary value problems for systems of shallow-water equations. Using the testfunction method proposed by Pokhozhaev and Mitidieri, we study the effects of the boundary values and initial conditions on the occurrence, duration, and rate of blowup of the solutions of these problems. Under natural boundary conditions, we prove the existence of blowup in one- and two-dimensional problems in bounded and unbounded regions with dissipation and dispersion.     

关于广义Newton法的收敛性问题

本文在较弱的条件下,证明了Ｂ－可微方程组的广义Ｎｅｗｔｏｎ法的局部超线性收敛性,为该算法直接应用于非线性规划问题、变分不等问题以及非线性互补问题等提供了理论依据。最后,本文给出了广义Ｎｅｗｔｏｎ法付之实践的具体策略。数值结果表明,算法是行之有效的。     

Computing equilibria of Cournot oligopoly models with mixed-integer quantities

We consider Cournot oligopoly models in which some variables represent indivisible quantities. These models can be addressed by computing equilibria of Nash equilibrium problems in which the players solve mixed-integer nonlinear problems. In the literature there are no methods to compute equilibria of this type of Nash games. We propose a Jacobi-type method for computing solutions of Nash equilibrium problems with mixed-integer variables. This algorithm is a generalization of a recently proposed method for the solution of discrete so-called “2-groups partitionable” Nash equilibrium problems. We prove that our algorithm converges in a finite number of iterations to approximate equilibria under reasonable conditions. Moreover, we give conditions for the existence of approximate equilibria. Finally, we give numerical results to show the effectiveness of the proposed method.     

一类广义半无限规划问题的光滑牛顿算法

本文在广义半无限规划问题的最优解集X处满足某些条件的前提下将广义半无限规划问题转化成KKT系统,通过扰动的FB函数,将KKT系统转化为一组光滑函数方程,设计了一个光滑牛顿算法,证明了算法的全局收敛性,并且在光滑函数解集处满足局部误差界条件下证明了算法具有超线性收敛速率.     

Comparison of Two Sets of First-Order Conditions as Bases of Interior-Point Newton Methods for Optimization with Simple Bounds

In this paper, we compare the behavior of two Newton interior-point methods derived from two different first-order necessary conditions for the same nonlinear optimization problem with simple bounds. One set of conditions was proposed by Coleman and Li; the other is the standard KKT set of conditions. We discuss a perturbation of the CL conditions for problems with one-sided bounds and the difficulties involved in extending this to problems with general bounds. We study the numerical behavior of the Newton method applied to the systems of equations associated with the unperturbed and perturbed necessary conditions. Preliminary numerical results for convex quadratic objective functions indicate that, for this class of problems, the Newton method based on the perturbed KKT formulation appears to be the more robust.     

Optimal control computation for parabolic systems with boundary conditions involving time delays

In this paper, we consider a class of optimal control problems involving a second-order, linear parabolic partial differential equation with Neumann boundary conditions. The time-delayed arguments are assumed to appear in the boundary conditions. A necessary and sufficient condition for optimality is derived, and an iterative method for solving this optimal control problem is proposed. The convergence property of this iterative method is also investigated.On the basis of a finite-element Galerkin's scheme, we convert the original distributed optimal control problem into a sequence of approximate problems involving only lumped-parameter systems. A computational algorithm is then developed for each of these approximate problems. For illustration, a one-dimensional example is solved.     

Characteristic problems with normal derivatives for hyperbolic systems

We consider characteristic problems with normal derivatives for a hyperbolic systemwith two independent variables. Using the Riemann method, we obtain solvability conditions for these problems accurate to several arbitrary constants.