多目标半定规划的最优性条件及对偶理论

在不变凸的假设下来讨论多目标半定规划的最优性条件、对偶理论以及非凸半定规划的最优性条件．首先给出了非凸半定规划的一个KKT条件成立的充分必要条件, 并利用此定理证明了其最优性必要条件．其次讨论了多目标半定规划的最优性必要条件、充分条件, 并对其建立Wolfe对偶模型, 证明了弱对偶定理和强对偶定理．     

泛函中的两个对偶定理

本文利用＊隔离定理,证明了Ｍａｚｕｒ定理和凸集的最佳逼近元存在性定理的对偶定理．     

F─广义凸多目标规划的对偶理论

本文讨论Ｆ—广义凸多目标规划的对偶理论，证明了弱对偶、直接对偶和逆对偶定理．主要结果参考文献［１］的推广和发展。     

一类分式线性规划问题的对偶规划与算法

给出线性分式规划问题的对偶规划与对偶定理，由此得到一个解线性分式规划的方法．     

一类非光滑优化问题的最优性与对偶（英文）

本文研究了一类带等式和不等式约束的非光滑多目标优化问题,给出了该类问题的Karush-Kuhn-Tucker最优性必要条件和充分条件,建立了该类规划问题的一类混合对偶模型的弱对偶定理、强对偶定理、逆对偶定理、严格逆对偶定理和限制逆对偶定理.     

一类非光滑优化问题的最优性与对偶

本文研究了一类带等式和不等式约束的非光滑多目标优化问题,给出了该类问题的Karush-Kuhn-Tucker最优性必要条件和充分条件,建立了该类规划问题的一类混合对偶模型的弱对偶定理、强对偶定理、逆对偶定理、严格逆对偶定理和限制逆对偶定理.     

非光滑伪线性多目标规划对偶

本文利用Ｄｉｎｉ右上、右下导数给出了非光滑伪线性多目标规划的对偶理论，建立了Ｍｏｎｄ－Ｗｅｉｒ型对仍与Ｗｏｌｆ型对偶；并证明了原问题与对偶问题之间的对偶定理．     

含有BF—I函数的多目标变分问题的混合对偶性

在有效解的意义下,对一类含有BF—I函数的多目标变分问题给出了混合型对偶的强对偶定理、弱对偶定理和严格逆对偶定理。     

向量最优化问题的Lagrange对偶与择一定理

本文讨论无限维向量最优化问题的Lagrange对偶与弱对偶，建立了若干鞍点定理与弱鞍点定理．作为研究对偶问题的工具，建立了一个新的择一定理．     

广义I型连通级小极大分式问题的对偶

在I型弧连通和广义I型弧连通假设下,建立了极大极小分式优化问题的对偶模型,并提出了弱对偶定理、强对偶定理和严格逆对偶定理.     

A Generalization of De Vries Duality Theorem

Generalizing Duality Theorem of H. de Vries, we define a category which is dually equivalent to the category of locally compact Hausdorff spaces and perfect maps.     

Farkas' Lemma, other theorems of the alternative, and linear programming in infinite-dimensional spaces: a purely linear-algebraic approach

We briefly consider several formulations of Farkas' Lemma first. Then we assume the setting of two vector spaces, one of them being linearly ordered, over a linearly ordered field till the end of this article. In this setting, we state a generalized version of Farkas' Lemma and prove it in a purely linear-algebraic way. Afterwards, we present Theorems of Motzkin, Tucker, Carver, Dax, and some other theorems of the alternative that characterize consistency of a finite system of linear inequalities. We also mention the Key Theorem, which is a related result. Finally, we use Farkas' Lemma to prove the Duality Theorem for linear programming (with a finite number of linear constraints). The Duality Theorem that is proved here covers, among others, linear programming in a real vector space of finite or infinite dimension and lexicographic linear programming.     

Full does not imply strong, does it?

We give a duality for the variety of bounded distributive lattices that is not full (and therefore not strong) although it is full but not strong at the finite level. While this does not give a complete solution to the “Full vs Strong” Problem, which dates back to the beginnings of natural duality theory in 1980, it does solve it at the finite level. One consequence of this result is that although there is a Duality Compactness Theorem, which says that if an alter ego of finite type yields a duality at the finite level then it yields a duality, there cannot be a corresponding Full Duality Compactness Theorem. Received October 1, 2002; accepted in final form November 10, 2004.     

Nontrivial solutions for elliptic resonant problems

Nontrivial solutions for elliptic resonant problems are obtained via Morse theory. To compute the critical groups at infinity of the relevant functional, we propose a new approach by combining the homotopy and reduction methods, and the Alexander Duality Theorem.     

History and Evolution of the Density Theorem for Gabor Frames

The Density Theorem for Gabor Frames is one of the fundamental results of time-frequency analysis. This expository survey attempts to reconstruct the long and very involved history of this theorem and to present its context and evolution, from the one-dimensional rectangular lattice setting, to arbitrary lattices in higher dimensions, to irregular Gabor frames, and most recently beyond the setting of Gabor frames to abstract localized frames. Related fundamental principles in Gabor analysis are also surveyed, including the Wexler-Raz biorthogonality relations, the Duality Principle, the Balian-Low Theorem, the Walnut and Janssen representations, and the Homogeneous Approximation Property. An extended bibliography is included.     

The dependency diagram of a linear programme

The Dependency Diagram of a Linear Programme (LP) shows how the successive inequalities of an LP depend on former inequalities, when variables are projected out by Fourier–Motzkin Elimination. It is also explained how redundant inequalities can be removed, using the method attributed to Chernikov and to Kohler. Some new results are given. The procedure also leads to a transparent explanation of Farkas’ Lemma, LP Duality, the dual form of Caratheodory’s Theorem as well as generating all vertices and extreme rays of the Dual Polytope.     

Lexicographical order and duality in multiobjective programming

This paper studies the applications of lexicographical order relation for vectors in the mathematical theory of multiobjective programming. We show that any Pareto minimum of an unconstrained convex. problem is the lexicographical minimum for the problem associated to a matrix multiplier having lexicographical positive columns. A similar result is also obtained for inequality constrained problems.Our approach to the theory of duality follows the pattern of Jahn [3], but we substitute vectors by matrices in the formulation of the dual problem and the usual scalar order relation by the lexicographical order relation. This allows us to state the Strong Duality Theorem in terms of Pareto minima and to eliminate some regularity assumptions.     

Sum theorems for monotone operators and convex functions

In this paper, we derive sufficient conditions for the sum of two or more maximal monotone operators on a reflexive Banach space to be maximal monotone, and we achieve this without any renorming theorems or fixed-point-related concepts. In the course of this, we will develop a generalization of the uniform boundedness theorem for (possibly nonreflexive) Banach spaces. We will apply this to obtain the Fenchel Duality Theorem for the sum of two or more proper, convex lower semicontinuous functions under the appropriate constraint qualifications, and also to obtain additional results on the relation between the effective domains of such functions and the domains of their subdifferentials. The other main tool that we use is a standard minimax theorem.