Antieigenvalues and total antieigenvalues of normal operators

We will study antieigenvalues, total antieigenvalues, antieigenvectors, and total antieigenvectors for normal operators. This will generalize the earlier work of the author and Karl Gustafson on normal matrices on finite dimensional spaces. We will also study antieigenvalues and total antieigenvalues of semigroups generated by accretive normal operators.     

Duality and saddle-points for convex-like vector optimization problems on real linear spaces

Usually, finite dimensional linear spaces, locally convex topological linear spaces or normed spaces are the framework for vector and multiojective optimization problems. Likewise, several generalizations of convexity are used in order to obtain new results. In this paper we show several Lagrangian type duality theorems and saddle-points theorems. From these, we obtain some characterizations of several efficient solutions of vector optimization problems (VOP), such as weak and proper efficient solutions in Benson’s sense. These theorems are generalizations of preceding results in two ways. Firstly, because we consider real linear spaces without any particular topology, and secondly because we work with a recently appeared convexlike type of convexity. This new type, designated GVCL in this paper, is based on a new algebraic closure which we named vector closure. This research for the second author was partially supported by Ministerio de Ciencia y Tecnología (Spain), project BFM2003-02194.     

集值B－H－S变分不等式及其应用

本文在Ｄａｎａｃｈ空间中，研究了集值Ｂ－Ｈ－Ｓ变分不等式问题和相补问题．将有限维空间、单值映象的若干结果改进并推广到无穷维空间．利用本文获得的结果．我们解决了无穷维空间中的鞍点问题和两类规划问题．     

广义凸空间内的非紧无限最优化和约束对策的平衡

由应用作者得到的拟平衡问题的一个新的存在性定理,在没有线性结构的广义凸空间内对非紧无限最优化问题和非紧约束对策问题证明了解的存在性定理。这些定理改进和推广了最近文献中许多重要结果。     

奇数维spin~c流形和S~1作用(英文)

本文研究了奇数维spin~c流形上的等边指标定理.用这些指标定理和一些复分析的讨论,得到了两个奇数维spin~c流形上的Atiyah-Hirzebruch类型消灭定理,结果推广了刘-王的消灭定理.     

Variational Inequality and Complementarity Problem for Set－Valued Mapping with Application

ＶａｒｉａｔｉｏｎａｌＩｎｅｑｕａｌｉｔｙａｎｄＣｏｍｐｌｅｍｅｎｔａｒｉｔｙＰｒｏｂｌｅｍｆｏｒＳｅｔ－ＶａｌｕｅｄＭａｐｐｉｎｇｗｉｔｈＡｐｐｌｉｃａｔｉｏｎ￥ＺｈａｎｇＣｏｎｇｊｕｎ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，Ｈｕａｉｂｅ...     

Quasi-equilibrium problems with applications to infinite optimization and constrained games in general topological spaces

By applying a new Fan-Browder type fixed point point theorem due to author, an existence theorem of quasi-equilibrium problem is proved in general topological space. As applications, some existence theorems of solutions for noncompact infinite optimization problems and noncompact constrained game problems are obtained in general topological spaces. These theorems improve and generalize a number of important results in recent literature.     

无线通信系统设计中的两个优化问题和相关优化方法

无线通信系统设计中的许多问题可建模为优化问题.一方面,这些优化问题常常具有高度的非线性性,一般情况下难于求解;另一方面,它们又有自身的特殊结构,例如隐含的凸性、可分性等.利用优化的方法结合问题的特殊结构求解和处理无线通信系统设计问题是近年来学术界研究的热点.本文重点讨论无线通信系统设计中的两个优化问题和相关优化方法,包括多用户干扰信道最大最小准则下的联合传输/接收波束成形设计和多输入多输出(Multi-Input Multi-Output,MIMO)检测问题,主要介绍现代优化技术结合问题的特殊结构在求解和处理上述两个问题的最新进展.     

强不可约算子理论及其应用(英文)

在有限维空间的矩阵理论中,著名的约当标准型定理充分揭示了矩阵的内在结构.在这篇综述中,我们给出复可分的无穷维希尔伯特空间上类似的约当标准型定理.同时也展示了该理论在其它数学分支中的应用。     

Verallgemeinerte Regelflächen im Grossen II

In Euclidean n-space we prove two vertex theorems for simply closed generalized ruled surfaces. The statements refer to the minimum of generators with special geometrical properties, and generalize theorems of SABAN[9] about ruled surfaces in Euclidean 3-space. Two examples are given.

---

---

Herrn Prof. Dr. Karl Strubecker zum 80. Geburtstag     

An approximation technique for robust nonlinear optimization

Nonlinear equality and inequality constrained optimization problems with uncertain parameters can be addressed by a robust worst-case formulation that is, however, difficult to treat computationally. In this paper we propose and investigate an approximate robust formulation that employs a linearization of the uncertainty set. In case of any norm bounded parameter uncertainty, this formulation leads to penalty terms employing the respective dual norm of first order derivatives of the constraints. The main advance of the paper is to present two sparsity preserving ways for efficient computation of these derivatives in the case of large scale problems, one similar to the forward mode, the other similar to the reverse mode of automatic differentiation. We show how to generalize the techniques to optimal control problems, and discuss how even infinite dimensional uncertainties can be treated efficiently. Finally, we present optimization results for an example from process engineering, a batch distillation.     

Matrix decomposition algorithms for elliptic boundary value problems: a survey

We provide an overview of matrix decomposition algorithms (MDAs) for the solution of systems of linear equations arising when various discretization techniques are applied in the numerical solution of certain separable elliptic boundary value problems in the unit square. An MDA is a direct method which reduces the algebraic problem to one of solving a set of independent one-dimensional problems which are generally banded, block tridiagonal, or almost block diagonal. Often, fast Fourier transforms (FFTs) can be employed in an MDA with a resulting computational cost of O(N ² logN) on an N × N uniform partition of the unit square. To formulate MDAs, we require knowledge of the eigenvalues and eigenvectors of matrices arising in corresponding two–point boundary value problems in one space dimension. In many important cases, these eigensystems are known explicitly, while in others, they must be computed. The first MDAs were formulated almost fifty years ago, for finite difference methods. Herein, we discuss more recent developments in the formulation and application of MDAs in spline collocation, finite element Galerkin and spectral methods, and the method of fundamental solutions. For ease of exposition, we focus primarily on the Dirichlet problem for Poisson’s equation in the unit square, sketch extensions to other boundary conditions and to more involved elliptic problems, including the biharmonic Dirichlet problem, and report extensions to three dimensional problems in a cube. MDAs have also been used extensively as preconditioners in iterative methods for solving linear systems arising from discretizations of non-separable boundary value problems.     

New techniques for cost sharing in combinatorial optimization games

Combinatorial optimization games form an important subclass of cooperative games. In recent years, increased attention has been given to the issue of finding good cost shares for such games. In this paper, we define a very general class of games, called integer minimization games, which includes the combinatorial optimization games in the literature as special cases. We then present new techniques, based on row and column generation, for computing good cost shares for these games. To illustrate the power of these techniques, we apply them to traveling salesman and vehicle routing games. Our results generalize and unify several results in the literature. The main underlying idea is that suitable valid inequalities for the associated combinatorial optimization problems can be used to derive improved cost shares.     

Multiobjective bilevel optimization

In this work nonlinear non-convex multiobjective bilevel optimization problems are discussed using an optimistic approach. It is shown that the set of feasible points of the upper level function, the so-called induced set, can be expressed as the set of minimal solutions of a multiobjective optimization problem. This artificial problem is solved by using a scalarization approach by Pascoletti and Serafini combined with an adaptive parameter control based on sensitivity results for this problem. The bilevel optimization problem is then solved by an iterative process using again sensitivity theorems for exploring the induced set and the whole efficient set is approximated. For the case of bicriteria optimization problems on both levels and for a one dimensional upper level variable, an algorithm is presented for the first time and applied to two problems: a theoretical example and a problem arising in applications.     

Elliptic quadratic forms,focal points,and a generalized theory of oscillation

The purpose of this paper is to generalize the theory, methods, and results for oscillation of second-order normal ordinary differential equations. This purpose is obtained by use of a theory of quadratic forms on Hilbert spaces given by Hestenes and the author.In particular, the ideas of this paper may be applied to second-order abnormal problems of differential equations, higher-order control problems, integral and partial differential equations, abstract approximation problems, and to finite dimensional approximations which lead to meaningful computer algorithms.For expository purposes some examples are included. Finally we show that specific existence and comparison theorems for the second-order case may be generalized to the 2nth-order case.     

The inverse problem for Krein orthogonal matrix functions

In the mid-fifties, in a seminal paper, M. G. Krein introduced continuous analogs of Szeg? orthogonal polynomials on the unit circle and established their main properties. In this paper, we generalize these results and subsequent results that he obtained jointly with Langer to the case of matrix-valued functions. Our main theorems are much more involved than their scalar counterparts. They contain new conditions based on Jordan chains and root functions. The proofs require new techniques based on recent results in the theory of continuous analogs of resultant and Bezout matrices and solutions of certain equations in entire matrix functions.     

On the (N+1)-dimensional local fractional reduced differential transform method and its applications

In this paper, we generalize the (N+1)-dimensional local fractional reduced differential transform method (LFRDTM) within the local fractional derivative sense. First, we show some new properties, lemmas, theorems and corollariesfor the (N+1)-dimensional LFRDTM. Second, these new properties, lemmas and theorems can be proved immediately after. Thirdly, we used two examples to state that this approach is efficient and simple to find numerical solutions to higher dimensional local fractional partial differential equations. Finally, we can be seen that this work can be looked as an extension of the prior work.     

Maximally monotone linear subspace extensions of monotone subspaces: explicit constructions and characterizations

Monotone linear relations play important roles in variational inequality problems and quadratic optimizations. In this paper, we give explicit maximally monotone linear subspace extensions of a monotone linear relation in finite dimensional spaces. Examples are provided to illustrate our extensions. Our results generalize a recent result by Crouzeix and Ocaña-Anaya.     

乘积拓扑空间内的重合点组定理及应用(Ⅰ)

首先引入了无凸性结构的有限连续拓扑空间(简称FC-空间)新概念．其次在FC-空间内建立了一个新的连续选择定理．应用此定理,在很弱的假设下,对定义在非紧FC-空间的乘积空间上的两个集值映射簇证明了某些新的重合点定理．这些结果推广了最近文献中的许多已知结果．某些应用将在后继文章中给出．     

On a characterization of convexity-preserving maps, Davidon’s collinear scalings and Karmarkar’s projective transformations

In a recent paper, the authors have proved results characterizing convexity-preserving maps defined on a subset of a not-necessarily finite dimensional real vector space as projective maps. The purpose of this note is three-fold. First, we state a theorem characterizing continuous, injective, convexity-preserving maps from a relatively open, connected subset of an affine subspace of ℝ ^m into ℝ ⁿ as projective maps. This result follows from the more general results stated and proved in a coordinate-free manner in the above paper, and is intended to be more accessible to researchers interested in optimization algorithms. Second, based on that characterization theorem, we offer a characterization theorem for collinear scalings first introduced by Davidon in 1977 for deriving certain algorithms for nonlinear optimization, and a characterization theorem for projective transformations used by Karmarkar in 1984 in his linear programming algorithm. These latter two theorems indicate that Davidon’s collinear scalings and Karmarkar’s projective transformations are the only continuous, injective, convexity-preserving maps possessing certain features that Davidon and Karmarkar respectively desired in the derivation of their algorithms. The proofs of these latter two theorems utilize our characterization of continuous, injective, convexity-preserving maps in a way that has implications to the choice of scalings and transformations in the derivation of optimization algorithms in general. The third purpose of this note is to point this out. Received: January 2000 / Accepted: November 2000?Published online January 17, 2001