Banach空间迭代序列的收敛性

先对相关基础知识进行了介绍说明,如拟增生类映象和压缩类映象,广义Lipschitz,两种迭代的迭代过程.然后阐述了目前已知相关结果,给出并论证了Mann迭代序列的收敛性.即在一致光滑的实Banach空间中,讨论并研究了带误差的Mann迭代逼近广义Lipschitz广义Φ-半压缩映象不动点的问题,改进和推广了现有的结果.     

广义Lipschitz多值渐近Ф-半压缩映象不动点集的迭代程序

设K是实Banach空间E中的有界邻近子集，多值映象T1，T2：K→2^K是广义一致L—Lipschitz的渐近乒半压缩映象，且T1一致连续．证明了具误差的Ishikawa型迭代集合序列强收敛到T1，T2的公共不动点集．同时，证明了当T：K→2置是一致连续的广义Lipschitz强增生算子时，具误差的Ishikawa型迭代列强收敛到方程Tx=f的解．     

半群中的Lipschitz各态历经和广义各态历经

本文利用链回复性研究连续映射迭代形成的半群上Lipschitz各态历经和广义各态历经,分别给出Lipschitz各态历经和广义各态历经的充分必要条件,并举例说明各态历经、广义各态历经和Lipschitz各态历经性的关系.     

广义LipschitzΦ-增生算子的带误差项的Ishikawa迭代序列的收敛性及应用

在一致光滑Banach空间中,证明了广义LipschitzΦ-增生算子的带误差项的Ishikawa迭代序列强收敛于方程Tx=f的解,其结果改进和扩展了近期许多相关结果.并由此得出了Ishikawa迭代序列稳定性的一些结果.     

一致光滑Banach空间中Ф-半压缩映射具误差Mann迭代收敛定理的注释

文章在一致光滑Banach空间,获得了广义LipschitzΦ-半压缩映射带误差的Mann迭代收敛定理.该结果改进并拓广了文献[1,7,10-12]中相应的结果.     

一类广义非线性混合拟变分包含组

本文引入了一类新的带松弛单调映射和松弛Lipschitz映射的广义非线性混合拟变分包含组 ,构造了求解该类变分包含组的迭代算法 ,证明了该类变分包含组解的存在性以及由本文构造的迭代算法产生的迭代序列的强收敛性 .所得结果推广和改进了大量文献中的最新结果[1 5 ] .     

g-Eta-单调映像和解广义隐似变分包含的预解算子技巧

引入一类新的g-Eta-单调映像和一类涉及g-Eta-单调映像的广义隐似变分包含；定义了g-Eta-单调映像的预解算子，并证明了其Lipschitz连续性；分析和给出了这类涉及g-Eta-单调映像的广义隐似变分包含的迭代算法，并证明了其收敛性．     

非Lipschitz的广义渐近φ-半压缩映象迭代序列的强收敛性

在较一般的条件下,研究了赋范线性空间中具误差的修正的Mann迭代程序逼近非Lipschitz的广义渐近φ-半压缩映象不动点的强收敛性.所得结果推广和改进了近期内的相应结果.     

一致等度连续的渐近拟伪压缩型映象的强收敛性

设E是实赋范线性空间.K是E中的非空凸子集.T1,T2是K上的自映象.当T1是一致等度连续的渐近拟伪压缩型映象,T2是广义一致Lipschitz映象时,研究了具误差的Isikawa型迭代序列强收敛于T1,T2公共不动点的充要条件.所得结果推广和改进了近期内的相应结果.     

强(A,η)-增生算子及其在变分包含中的应用

本文引入一类广义增生算子——强(A,η)-增生算子.定义强(A,η)-增生算子的广义预解算子并证明它的Lipschitz连续性,进一步证明含强(A,η)-增生算子的变分包含的一些新的迭代算法的收敛性.所得结果改进和推广了许多文献的相应结果.     

一类广义Lipschitz非线性算子的带误差的Ishikawa迭代程序

借助于周海云和陈东青［４］新近引入的广义Ｌｉｐｓｃｈｉｔｚ概念,研究了实Ｂａｎａｃｈ空间中广义Ｌｉｐｓｃｈｉｔｚ　 －强伪压缩算子的不动点和广义Ｌｉｐｓｃｈｉｔｚ －强增算子方程解的迭代逼近问题,所得结果改进和扩展了近期许多相关的结果,并部分地回答了周海云［３］提出的一个问题．     

非光滑优化的二阶必要条件

1 引言 对无约束最优化问题,其必要条件要求在局部极小点x处沿任何方向的梯度为零,曲率为正。而对约束最优化问题,首先它的局部极小点必须是可行点,其次不仅要求验证局部 极小点的某个邻域内的二阶项(曲率),而且也要认识到约束曲率也起相当重要的作用。现实中存在这样的问题,在x点处G正定,而它不是局部极小点。因此必须考虑约束最优化问题的二阶必要性条件。 本文研究了非线性规划的二阶必要性条件,其约束函数的一阶导数为方向Lipschitz连续。 2 方向Lipschitz连续函数的性质 定义2.1 设f是R~n上的一个广义实值函数,f在x∈R~n处有限,称f在x处是方向Lipschitz连续的,如果至少存在一点y∈R~n使得 其中( 定义2.2 设f如定义2.1,定义f在R~n处的次导数集如下 其中 本文多次引用f↑(x;y),因此我们首先介绍f↑(x;y)的3个基本性质:     

Coderivative Analysis of Variational Systems

The paper mostly concerns applications of the generalized differentiation theory in variational analysis to Lipschitzian stability and metric regularity of variational systems in infinite-dimensional spaces. The main tools of our analysis involve coderivatives of set-valued mappings that turn out to be proper extensions of the adjoint derivative operator to nonsmooth and set-valued mappings. The involved coderivatives allow us to give complete dual characterizations of certain fundamental properties in variational analysis and optimization related to Lipschitzian stability and metric regularity. Based on these characterizations and extended coderivative calculus, we obtain efficient conditions for Lipschitzian stability of variational systems governed by parametric generalized equations and their specifications.     

局部凸空间上的泛函的非光滑分析及多目标规划

该文对定义于局部凸线性拓扑空间Ｘ上的泛函引入广义方向导数、广义梯度及满足Ｌｉｐｓ－ｃｈｉｔｚ条件等概念,证明了它们的几个重要性质,并举例说明这里满足Ｌｉｐｓｃｈｉｔｚ条件的概念是Ｂａ－ｎａｃｈ空间情形的严格推广．最后,作为上述结论及方法的应用,讨论定义于Ｘ的多目标数学规划,得出若干关于弱有效解的最优性条件．     

一类具有广义Lipschitz条件的非线性映象的迭代过程

本文研究了广义Ｌｉｐｓｃｈｉｔｚ强增生映象的Ｉｓｈｉｋａｗａ型迭代和Ｍａｎｎ型迭代过程的收敛性．所得结果统一和扩展了近期相关结果     

Generalized sequential normal compactness in Banach spaces

Normal compactness conditions are important properties of sets, set-valued mappings in variational analysis, which are generalized versions of the classical Lipschitzian property and are essential for the calculus of generalized differentiation theory. In this paper we propose the notion called the generalized sequential normal compactness, and establish its basic properties and calculus in general Banach spaces.     

Fixed points of semigroups of Lipschitzian mappings defined on nonconvex domains

Certain fixed point theorems are established for nonlinear semigroups of Lipschitzian mappings defined on nonconvex domains in Hilbert and Banach spaces. Some known results are thus generalized.     

两种微分形式下最优性条件的关系

本文考虑具有不等式约束条件不可微优化问题，假定目标函数和约束函数既是Lipschitz的也是拟可微的．证明了该问题拟微分形式下的FritzJohn点必是Clarke广义梯度形式下的FritzJohn点．另外，还给出了拟微分和Clarke广义梯度之间的关系．     

Generalized Newton’s method based on graphical derivatives

This paper concerns developing a numerical method of the Newton type to solve systems of nonlinear equations described by nonsmooth continuous functions. We propose and justify a new generalized Newton algorithm based on graphical derivatives, which have never been used to derive a Newton-type method for solving nonsmooth equations. Based on advanced techniques of variational analysis and generalized differentiation, we establish the well-posedness of the algorithm, its local superlinear convergence, and its global convergence of the Kantorovich type. Our convergence results hold with no semismoothness and Lipschitzian assumptions, which is illustrated by examples. The algorithm and main results obtained in the paper are compared with well-recognized semismooth and B-differentiable versions of Newton’s method for nonsmooth Lipschitzian equations.     

Lipschitzian stability of fully parameterized generalized equations

This paper concerns the study of Lipschitzian stability of fully parameterized generalized equations in which both single-valued and set-valued functions depend on parameters. Various relationships between the Lipschitz-like and metric regularity properties of the solution mapping, the base mapping, or field mapping in the fully perturbed generalized equations are established by using the Dontchev–Hager Fixed Point Theorem. The implicit mapping theorem for metric regularity is also extended to fully parameterized generalized equations.