关于多目标数学规划的最优性条件

本文讨论定义于Ｂａｎａｃｈ空间的多目标数学规划，得到一些ε－最优解和（弱）有效解的必要条件，充分条件和必要充分条件。     

非可微凸规划的对偶问题

文章建立关于非可微凸规划的一个新的对偶问题,它不同于已知的对偶问题,文中证明了弱对偶性及强对偶性。并用Ｌａｇｒａｎｇｅ正则性证明了强对偶性的充要条件。最后,讨论了等式约束的情况。     

不可微凸规划问题Lagrange乘子的存在性与值函数的次可微性

本文讨论了一类非光滑凸规划问题，给出了Ｌａｇｒａｎｇｅ乘子的存在性与值函数的次可微性的关系和乘子存在的充分条件。     

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．     

多目标半定规划的互补弱鞍点和G-鞍点最优性条件

对于含矩阵函数半定约束和多个目标函数的多目标半定规划问题，给出Lagrange函数在弱有效意义下的互补弱鞍点和Geofrrion恰当有效意义下的G-鞍点的定义及其等价定义．然后，在较弱的凸性条件下，利用含矩阵和向量约束的择一性定理，建立多目标半定规划的互补弱鞍点和G-鞍点充分必要条件．     

ε－次可微多目标规划的最优性条件

本文主要从多目标规划相应的加权问题出发，讨论了在ε－次可微的条件下，凸多目标规划问题η－有效解存在的必要条件与充分条件．     

关于FRITZ JOHN条件

本文证明多目标问题的有效解总适合 Fritz John必要条件 ,并利用单目标规划问题最优解的一个新的 Fritz John充分条件推出多目标问题有效解的两个新的充分条件     

关于求解带线性互补约束的数学规划问题正则方法的一个注记

本文主要研究在某些较弱条件下求解带线性互补约束的数学规划问题(MPLCC)正则方法的收敛性.若衡约束规划线性独立约束规范条件(MPEC-LICQ)在由正则方法产生的点列的聚点处成立,且迭代点列满足二阶必要条件,同时,若比在文[7]中渐近弱非退化条件Ⅰ更弱的渐近弱非退化条件Ⅱ在聚点处也成立,那么所有这些聚点都是B-稳定点.此外,在弱MPEC-LICQ,二阶必要条件及渐近弱退化条件Ⅱ下,我们仍能证明通过正则方法所得的聚点都是B-稳定点.     

正则局部Lipschitz函数可微性的几何条件

Ｂａｎａｃｈ空间的范数可微性可用它的单位球面来刻画．本文把这些范数可微性的几何条件推广到正则局部Ｌｉｐｓｃｈｉｔｚ函数情形．     

非光滑多目标规划的最优性

本文给出了一种新的右上导数定义,利用这一右上导数定义了几类广义凸性条件,进而讨论了非光滑多目标规划的最优性．包括Ｆｒｉｔｚ－Ｊｏｈｎ条件和Ｋｕｈｎ－Ｔｕｃｋｅｒ条件．     

Another approach to multiobjective programming problems withF-convex functions

In this paper, optimality conditions for multiobjective programming problems havingF-convex objective and constraint functions are considered. An equivalent multiobjective programming problem is constructed by a modification of the objective function. Furthermore, anF—Lagrange function is introduced for a constructed multiobjective programming problem, and a new type of saddle point is introduced. Some results for the new type of a saddle point are given.     

多目标规划的对偶二阶条件

本文针对多目标规划 ( VP)的 Lagrange对偶规划 ( VD) ,从几何直观的角度出发 ,给出对偶规划( VD)的二阶最优性条件 ,即对偶二阶条件 ,并证明了相应的最优性定理 .     

A modified objective function method for solving nonlinear multiobjective fractional programming problems

A new method is used for solving nonlinear multiobjective fractional programming problems having V-invex objective and constraint functions with respect to the same function η. In this approach, an equivalent vector programming problem is constructed by a modification of the objective fractional function in the original nonlinear multiobjective fractional problem. Furthermore, a modified Lagrange function is introduced for a constructed vector optimization problem. By the help of the modified Lagrange function, saddle point results are presented for the original nonlinear fractional programming problem with several ratios. Finally, a Mond-Weir type dual is associated, and weak, strong and converse duality results are established by using the introduced method with a modified function. To obtain these duality results between the original multiobjective fractional programming problem and its original Mond-Weir duals, a modified Mond-Weir vector dual problem with a modified objective function is constructed.     

集值映射多目标半定规划的Benson真有效性

将多目标半定规划问题推广到集值映射,在广义锥-次类凸条件下,在Benson真有效性意义下研究了问题的标量化,Lagrange函数与无约束化,真鞍点条件和对偶性.     

Duality Theorems for Separable Convex Programming Without Qualifications

In the research of mathematical programming, duality theorems are essential and important elements. Recently, Lagrange duality theorems for separable convex programming have been studied. Tseng proves that there is no duality gap in Lagrange duality for separable convex programming without any qualifications. In other words, although the infimum value of the primal problem equals to the supremum value of the Lagrange dual problem, Lagrange multiplier does not always exist. Jeyakumar and Li prove that Lagrange multiplier always exists without any qualifications for separable sublinear programming. Furthermore, Jeyakumar and Li introduce a necessary and sufficient constraint qualification for Lagrange duality theorem for separable convex programming. However, separable convex constraints do not always satisfy the constraint qualification, that is, Lagrange duality does not always hold for separable convex programming. In this paper, we study duality theorems for separable convex programming without any qualifications. We show that a separable convex inequality system always satisfies the closed cone constraint qualification for quasiconvex programming and investigate a Lagrange-type duality theorem for separable convex programming. In addition, we introduce a duality theorem and a necessary and sufficient optimality condition for a separable convex programming problem, whose constraints do not satisfy the Slater condition.     

一类广义半无限规划问题的一阶最优性条件

本文利用一个精确增广Lagrange函数研究了一类广义半无限极小极大规划问题。在一定的条件下将其转化为标准的半无限极小极大规划问题。研究了这两类问题的最优解和最优值之间的关系,利用这种关系和标准半无限极小极大规划问题的一阶最优性条件给出了这类广义半无限极小极大规划问题的一个新的一阶最优性条件。     

多目标分式规划逆对偶研究

考虑了一类可微多目标分式规划问题.首先,建立原问题的两个对偶模型.随后,在相关文献的弱对偶定理基础上,利用Fritz John型必要条件,证明了相应的逆对偶定理.