不等式约束优化一个可行序列线性方程组算法

提出了求解非线性不等式约束优化问题的一个可行序列线性方程组算法.在每次迭代中,可行下降方向通过求解两个线性方程组产生,系数矩阵具有较好的稀疏性.在较为温和的条件下,算法具有全局收敛性和强收敛性,数值试验表明算法是有效的.     

数列极限迫敛性定理的推广(英文)

极限论是微积分中基础和重要的概念.数列极限的迫敛性定理既能判断数列的收敛性,也给出其极限值。通过对数列极限迫敛性定理的条件加以改进,得到了它的推论,并用一个例子说明了该推论的应用。     

求解非线性P_0互补问题的非单调磨光算法

提出了一种新的磨光函数,在分析它与已有磨光函数不同特性的基础上,研究了将它用于求解非线性P_0互补问题时,其磨光路径的存在性和连续性,进而设计了求解一类非线性P_0互补问题的非单调磨光算法.在适当的假设条件下,证明了该算法的全局收敛性和局部超线性收敛性.数值算例验证了算法的有效性.     

无约束极大极小问题的广义梯度投影算法

本文讨论Rⁿ空间上的无约束极大极小问题. 通过Rⁿ⁺¹空间上的广义梯度投影技术产生Rⁿ上的下降搜索方向,进而结合Armijo非精确线搜索建立了原问题Rⁿ上的一个广义梯度投影型算法.算法在仿射线性无关条件下,具有全局收敛性和强收敛性. 文中对算法进行了初步的数值试验.     

双障碍问题的多重网格法

本文研究双障碍问题的多重网格法,提出了两类算法,证明了其收敛性及对贴合分量的有限步收敛性,同时对其中一种算法的特款提出了一个 k无关收敛性定理。     

递推数列xn＋1=f（xn）的单调性与收敛性讨论

利用函数单调递增对递推数列xn＋1=f（xn）单调性进行讨论,在对递推数列收敛性作分析的基础上,得到使得递推数列收敛的初始迭代值的区域,讨论的方法可以用于类似问题的研究．     

递推数列x_(n+1)=f(x_n)的单调性与收敛性讨论

利用函数单调递增对递推数列xn+1=f(xn)单调性进行讨论,在对递推数列收敛性作分析的基础上,得到使得递推数列收敛的初始迭代值的区域,讨论的方法可以用于类似问题的研究.     

LF拓扑空间中的θ—收敛性（Ⅱ）

本文在LF拓扑空间中引进理想的θ-极限点和θ-聚点等概念,系统地研究理想的θ-收敛性的特征以及理想的θ-收敛性与分子网的θ-收敛性之间的关系。最后,利用理想的θ-收敛性刻画弱连续序同态、几乎连续序同态以及几乎F紧性。     

鞅差序列滑动和过程的极限结果

该文获得了鞅差序列滑动和过程的完全收敛性, Marcinkiewicz-Zygmund强大数定律, 矩完全收敛性以及讨论了极大值矩的存在性问题, 推广和改进了已有的结果.     

行为混合阵列加权和的收敛性

本文研究了行为混合阵列加权和的收敛性.利用混合序列的Rosenthal型最大值不等式,讨论了混合阵列加权和的L1收敛性,依概率收敛性,几乎处处收敛性,及完全收敛性之间的等价关系,推广了行独立随机变量阵列相应的结果.     

A BFGS algorithm for solving symmetric nonlinear equations

In this article, we propose a BFGS method for solving symmetric nonlinear equations. The presented method possesses some favourable properties: (a) the generated sequence of iterates is norm descent; (b) the generated sequence of the quasi-Newton matrix is positive definite and (c) this method possesses the global convergence and superlinear convergence. Numerical results show that the presented method is interesting.     

An Algorithm for Continuous Type Optimal Location Problem

In this paper, we extend the ordinary discrete type facility location problems to continuous type ones. Unlike the discrete type facility location problem in which the objective function isn't everywhere differentiable, the objective function in the continuous type facility location problem is strictly convex and continuously differentiable. An algorithm without line search for solving the continuous type facility location problems is proposed and its global convergence, linear convergence rate is proved. Numerical experiments illustrate that the algorithm suggested in this paper have smaller amount of computation, quicker convergence rate than the gradient method and conjugate direction method in some sense.     

Some Properties of Methods of Centers

Huard's method of centers is a method that solves constrained convex problems by means of unconstrained problems. In this paper we give some properties of this method, we analyse its convergence and rate of convergence and suggest some other variants and techniques to improve the speed of convergence.     

关于拟概率测度的收敛理论

本文研究了拟概率空间上收敛概念之间的关系这一问题.利用类比的方法,在拟概率空间上提出了一些新的关于拟-随机变量的收敛概念并讨论了这些收敛概念之间的关系,获得了模糊测度下的收敛理论,推广了关于经典测度的收敛概念.     

同时具有点和区间半径序列收敛性的免导迭代法的进一步讨论

1 引 言 传统的求零点的迭代法只讨论迭代序列{xn}的收敛阶,近年来,G.Alefeld和F.A.Po-tra研究了含零点的区间半径序列的收敛性[2][3],而我们提出了同时具有点和区间半径序列均平方收敛的免导迭代法[1],即当n充分大时,序列{xn}和含零点区间的半径序列{(bn-an)}都是平方收敛的.通过进一步的分析,我们发现,文[1]中的结果仍可改进,并且,不需     

HOMOCENTRIC CONVERGENCE BALL OF THE SECANT METHOD

A local convergence theorem and five semi-local convergence theorems of the secant method are listed in this paper.For every convergence theorem,a convergence ball is respectively introduced,where the hypothesis conditions of the corresponding theorem can be satisfied.Since all of these convergence balls have the same center x~*,they can be viewed as a homocentric ball. Convergence theorems are sorted by the different sizes of various radii of this homocentric ball, and the sorted sequence represents the degree of weakness on the conditions of convergence theorems.     

无约束优化问题的对角稀疏拟牛顿法

对无约束优化问题提出了对角稀疏拟牛顿法,该算法采用了Armijo非精确线性搜索,并在每次迭代中利用对角矩阵近似拟牛顿法中的校正矩阵,使计算搜索方向的存贮量和工作量明显减少,为大型无约束优化问题的求解提供了新的思路．在通常的假设条件下,证明了算法的全局收敛性,线性收敛速度并分析了超线性收敛特征。数值实验表明算法比共轭梯度法有效,适于求解大型无约束优化问题．     

Relationships between different types of initial conditions for simultaneous root finding methods

The construction of initial conditions of an iterative method is one of the most important problems in solving nonlinear equations. In this paper, we obtain relationships between different types of initial conditions that guarantee the convergence of iterative methods for simultaneously finding all zeros of a polynomial. In particular, we show that any local convergence theorem for a simultaneous method can be converted into a convergence theorem with computationally verifiable initial conditions which is of practical importance. Thus, we propose a new approach for obtaining semilocal convergence results for simultaneous methods via local convergence results.     

General Information

In this paper, we propose and analyze an SQP-type method for solving linearly constrained convex minimization problems where the objective functions are too complex to be evaluated exactly. Some basic results for global convergence and local superlinear convergence are obtained according to the properties of the approximation sequence. We illustrate the applicability of our approach by proposing a new method for solving two-stage stochastic programs with fixed recourse.     

带有广义Wolfe线搜索的变尺度算法的收敛性

本文提出一类广义Ｗｏｌｆｅ线搜索模型，并且把它与著名的ＢＦＧＳ方法相结合，对于所得到的算法证明了：对于凸函数算法具有全局收敛性和超线性收敛速度，这推广了参考文献［１］中的结果．