Hilbert空间上凸函数的上、下指数的共轭性质

本文引入Ｈｉｌｂｅｒｔ空间上非负凸函数具有一般性的上下指数的概念，得到相互共轭凸函数的上下指数的共轭性质，也讨论了由内积范数导出的正ｐ（ｐ＞１）次齐次函数与正ｑ（ｑ＞１，１ｐ＋１ｑ＝１）之间的关系     

Hilbert空间上凸函数的上、下指数的共轭性质

本引入Hilbert空间上非负凸函数具有一般性的上下指数的概念，得到相互共轭凸函数的上下指数的共轭性质。也讨论了由内积范数导出的正p(p>1)次齐状函数与正q(q>1，1/p 1/q=1)之间的关系。     

关于模糊值凸函数的共轭问题的研究

在Goetschel-Voxman所引进的序关系下,首先给出了模糊值凸函数的共轭函数的概念,并证明了模糊值凸函数的共轭函数是模糊值凸函数等相关性质;其次给出了模糊值凸函数的二次共轭函数的概念,并证明了相关性质;最后讨论了模糊值凸函数的共轭与下卷积之间的关系,证明了两个模糊值凸函数的共轭函数与其下卷积的共轭函数之间的等式关系.     

模糊值m-凸函数的性质及其共轭问题的研究

基于m-凸函数提出了一类称为模糊值m-凸函数的新概念.首先,研究了模糊值m-凸函数的若干基本性质;其次,给出了模糊值m-凸函数的共轭函数的概念,并给出了模糊值m-凸函数在一定的条件下的共轭函数是模糊值m-凸函数等相关性质;最后,讨论了两个模糊值m-凸函数的共轭函数与其下卷积的共轭函数之间的相互关系.     

一个广义的共轭对偶

本文给出了广义的共轭概念,定义了规划问题的广义共轭对偶问题为;得到了强、弱对偶定理及极性条件的一些等价条件。在本文中,X表示一般非空集合,且H对逐点极大运算是封闭的; 定义1 函数f于x_0是H-Ω凸的是指,如f于X上任意点是H-Ω凸的,则称f是X上的H-Ω凸函数。由定义1得:H-Ω凸函数族的逐点极大函数也是H-Ω凸函数;对,则由     

指数凸函数的积分不等式及其在Gamma函数中的应用

仿对数凸函数的概念,给出指数凸函数的定义,并证明有关指数凸函数的几个积分不等式,作为应用,得到一个新的Kershaw型双向不等式.     

复指数系的完备性

对直线上的非负凸函数α,设Cα是由直线R上所有满足当t趋向无穷大时,f(t)exp(-α(t))趋向零的复连续函数f全体,在一致范数下,Cα是Banach空间.文中得到了复指数系在Cα中完备的充要条件.     

复指数系的完备性

对直线上的非负凸函数α,设Cα是由直线R上所有满足当t趋向无穷大时,f(t)exp(-α(t))趋向零的复连续函数f全体,在一致范数下,Cα是Banach空间.文中得到了复指数系在Cα中完备的充要条件.     

下凸函数两种定义等价性的一个证明

本文给出下凸函数两种定义等价性的一个证明,并导出了下凸函数的两个重要性质.对于上凸函数容易写出所有的相应结果.     

强G-半预不变凸函数的新性质探讨

本文讨论了强G-半预不变凸函数,它是强预不变凸函数与强G-预不变凸函数的真推广.首先,举例说明了强G-半预不变凸函数的存在性;然后,借助集合稠密性原理,获得了强G-半预不变凸函数的一个充要条件;最后,得到强G-半预不变凸函数在一定假设(在闭半连通集上)下的下确界就是函数在此集合上的最小值,所得结果推广并改进了相应文献中的结果.     

Some Farkas-type results for fractional programming problems with DC functions

For a kind of fractional programming problem that the objective functions are the ratio of two DC (difference of convex) functions with finitely many convex constraints, in this paper, its dual problems are constructed, weak and strong duality assertions are given, and some sufficient and necessary optimality conditions which characterize their optimal solutions are obtained. Some recently obtained Farkas-type results for fractional programming problems that the objective functions are the ratio of a convex function to a concave function with finitely many convex constraints are the special cases of the general results of this paper.     

An algorithm for the construction of convex hulls in simple integer recourse programming

We consider the objective function of a simple integer recourse problem with fixed technology matrix and discretely distributed right-hand sides. Exploiting the special structure of this problem, we devise an algorithm that determines the convex hull of this function efficiently. The results are improvements over those in a previous paper. In the first place, the convex hull of many objective functions in the class is covered, instead of only one-dimensional versions. In the second place, the algorithm is faster than the one in the previous paper. Moreover, some new results on the structure of the objective function are presented.     

一类特殊凸对策的求解方法

针对支付函数对每个自变量都是严格凸函数的一类特殊凸对策问题，提出了求解局中人双方最优策略的一种简单方法。     

Hessian measures of semi-convex functions and applications to support measures of convex bodies

This paper originates from the investigation of support measures of convex bodies (sets of positive reach), which form a central subject in convex geometry and also represent an important tool in related fields. We show that these measures are absolutely continuous with respect to Hausdorff measures of appropriate dimensions, and we determine the Radon-Nikodym derivatives explicitly on sets of σ-finite Hausdorff measure. The results which we obtain in the setting of the theory of convex bodies (sets of positive reach) are achieved as applications of various new results on Hessian measures of convex (semi-convex) functions. Among these are a Crofton formula, results on the absolute continuity of Hessian measures, and a duality theorem which relates the Hessian measures of a convex function to those of the conjugate function. In particular, it turns out that curvature and surface area measures of a convex body K are the Hessian measures of special functions, namely the distance function and the support function of K. Received: 15 July 1999     

Existence and sum decomposition of vertex polyhedral convex envelopes

Convex envelopes are a very useful tool in global optimization. However finding the exact convex envelope of a function is a difficult task in general. This task becomes considerably simpler in the case where the domain is a polyhedron and the convex envelope is vertex polyhedral, i.e., has a polyhedral epigraph whose vertices correspond to the vertices of the domain. A further simplification is possible when the convex envelope is sum decomposable, i.e., the convex envelope of a sum of functions coincides with the sum of the convex envelopes of the summands. In this paper we provide characterizations and sufficient conditions for the existence of a vertex polyhedral convex envelope. Our results extend and unify several results previously obtained for special cases of this problem. We then characterize sum decomposability of vertex polyhedral convex envelopes, and we show, among else, that the vertex polyhedral convex envelope of a sum of functions coincides with the sum of the vertex polyhedral convex envelopes of the summands if and only if the latter sum is vertex polyhedral.     

Higher-order generalized convexity and duality in nondifferentiable multiobjective mathematical programming

In this paper, a class of generalized convexity is introduced and a unified higher-order dual model for nondifferentiable multiobjective programs is described, where every component of the objective function contains a term involving the support function of a compact convex set. Weak duality theorems are established under generalized convexity conditions. The well-known case of the support function in the form of square root of a positive semidefinite quadratic form and other special cases can be readily derived from our results.     

Duality for location problems with unbounded unit balls

Given an optimization problem with a composite of a convex and componentwise increasing function with a convex vector function as objective function, by means of the conjugacy approach based on the perturbation theory, we determine a dual to it. Necessary and sufficient optimality conditions are derived using strong duality. Furthermore, as special case of this problem, we consider a location problem, where the “distances” are measured by gauges of closed convex sets. We prove that the geometric characterization of the set of optimal solutions for this location problem given by Hinojosa and Puerto in a recently published paper can be obtained via the presented dual problem. Finally, the Weber and the minmax location problems with gauges are given as applications.     

Convex composite multi-objective nonsmooth programming

This paper examines nonsmooth constrained multi-objective optimization problems where the objective function and the constraints are compositions of convex functions, and locally Lipschitz and Gâteaux differentiable functions. Lagrangian necessary conditions, and new sufficient optimality conditions for efficient and properly efficient solutions are presented. Multi-objective duality results are given for convex composite problems which are not necessarily convex programming problems. Applications of the results to new and some special classes of nonlinear programming problems are discussed. A scalarization result and a characterization of the set of all properly efficient solutions for convex composite problems are also discussed under appropriate conditions.This research was partially supported by the Australian Research Council grant A68930162.This author wishes to acknowledge the financial support of the Australian Research Council.     

A new constraint qualification for the formula of the subdifferential of composed convex functions in infinite dimensional spaces

In this paper we work in separated locally convex spaces where we give equivalent statements for the formulae of the conjugate function of the sum of a convex lower‐semicontinuous function and the precomposition of another convex lower‐semicontinuous function which is also K ‐increasing with a K ‐convex K ‐epi‐closed function, where K is a nonempty closed convex cone. These statements prove to be the weakest constraint qualifications given so far under which the formulae for the subdifferential of the mentioned sum of functions are valid. Then we deliver constraint qualifications inspired from them that guarantee some conjugate duality assertions. Two interesting special cases taken from the literature conclude the paper. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Ekeland's variational principle in locally convex spaces and the density of extremal points

In this paper, we prove a general version of Ekeland's variational principle in locally convex spaces, where perturbations contain subadditive functions of topology generating seminorms and nonincreasing functions of the objective function. From this, we obtain a number of special versions of Ekeland's principle, which include all the known extensions of the principle in locally convex spaces. Moreover, we give a general criterion for judging the density of extremal points in the general Ekeland's principle, which extends and improves the related known results.