生成锥内部凸-锥-类凸集值优化问题的超有效性

本文讨论生成锥内部凸-锥-类凸集值向量优化问题的超有效解.在生成锥内部凸-锥类凸假设下,建立了集值向量优化问题在超有效意义下的标量化、Lagrangian乘子和鞍点定理     

生成锥内部凸-锥-类凸集值优化问题的Henig真有效性

该文讨论局部凸空间中的约束集值优化问题. 首先, 在生成锥内部凸-锥-类凸假设下, 建立了Henig真有效解在标量化和Lagrange乘子意义下的最优性条件. 其次, 对集值Lagrange映射引入Henig真鞍点的概念, 并用这一概念刻画了Henig真有效解. 最后, 引入了一个标量Lagrange对偶模型, 并得到了关于Henig真有效解的对偶定理. 另外, 该文所得结果均不需要约束序锥有非空的内部.     

广义锥-s次类凸向量优化的标量化和鞍点定理

讨论序拓扑向量空间中的约束向量优化问题.在广义锥-s次类凸假设下,得到了向量优化问题关于δ-弱有效解的标量化定理和Lagrange泛函的鞍点定理.     

局部凸空间中ic -锥-类凸集值优化问题的超有效性

该文研究局部凸空间中受集值约束的集值优化问题的超有效解. 证明了ic -锥-类凸集值映射的一个有用性质, 并以此性质为主要工具, 得到了ic -锥-类凸集值向量优化问题超有效解的最优性条件和鞍点定理.     

近似锥-次类凸集值优化的严有效性

在Hausdorff局部凸拓扑线性空间中考虑约束集值优化问题(VP)的严有效性.在近似锥-次类凸假设下,利用凸集分离定理,分别得到了Kuhn-Tucker型和Lagrange型最优性条件,建立了与(VP)等价的两种形式的无约束优化.     

非凸集值优化问题严有效解的强对偶定理

本文研究了非凸集值向量优化的严有效解在两种对偶模型的强对偶问题.利用Lagrange对偶和Mond-Weir对偶原理,获得了如下结果：原集值优化问题的严有效解,在一些条件下是对偶问题的强有效解,并且原问题和对偶问题的目标函数值相等;推广了集值优化对偶理论在锥-凸假设下的相应结果.     

近似锥一次类凸集值向量优化问题强有效解的广义鞍点刻画

本文研究了近似锥一次类凸集值向量优化强有效解的广义鞍点表示问题.利用择一定理,得到了近似锥-次类凸集值优化问题强有效解为广义鞍点的充分条件和必要条件.所得结果丰富了集值优化理论,并且拓广了广义鞍点的应用.     

集值映射向量优化的Benson真有效性

本文首先将单值映射的锥次类凸概念推广到集值映射，并对锥次类凸集值映射给出几个等价刻划和一个择一性定理。然后，利用这些概念与结果来确定拓扑线性空间中带集值映射的向量优化问题的Ｂｅｎｓｏｎ真有效性，获得两个标量化结果和两个Ｌａｇｒａｎｇｅ乘子定理，在定义了一个适当的集值Ｌａｇｒａｎｇｅ映射并对其引入真鞍点的概念之后，又建立了Ｂｅｎｓｏｎ真有效性的一个充分条件和一个充要条件，最后还讨论了两个对偶问题。     

集值函数向量优化的鞍点条件

本文在局部凸拓扑向量空间中给出集值函数向量优化的鞍点条件。     

关于《集值优化问题Henig真有效解的最优性条件》一文的注记北大核心CSCD

本文指出《集值优化问题Henig真有效解的最优性条件》一文的主要结论是《近似锥-次类凸集值优化的严有效性》一文相应结论的特例.     

集值优化问题的Benson真有效解的广义导数型最优性条件

引进了集值映射关于锥的Clarke切导数, Adjacent切导数与Contingent切导数概念;应用它们导出了具Slater约束规格的集值优化问题的Benson真有效解的广义导数型最优性条件．     

Nearly Subconvexlike Set-Valued Maps and Vector Optimization Problems

This paper gives several characterizations of nearly subconvexlike set-valued maps (see Ref. 1) and shows that a weakly efficient solution and a Benson properly efficient solution of a vector optimization problem with nearly-subconvexlike objectives and constraints can be expressed in terms of saddle points defined in a suitable sense.     

Characterizations of the Benson Proper Efficiency for Nonconvex Vector Optimization

Under generalized cone-subconvexlikeness for vector-valued mappings in locally-convex Hausdorff topological vector spaces, a Gordan-form alternative theorem is derived. Some characterizations of the Benson proper efficiency under this generalized convexity are established in terms of scalarization, Lagrangian multipliers, saddle-point criterion, and duality.     

关于向量集值优化的Benson真有效性

对广义锥次数凸向量集值优化问题Benson真有效性解的标量化问题进行了研究,借助于一种新的择一性定理建立了广义锥次类凸向是集值优化问题Benson真有效解的Lagrange乘子型定理并讨论了乘子型对偶问题。     

集值优化问题的Benson真有效解的广义最优性条件

引进了关于集值映射的(1,α)-阶Clarke导数,(1,α)-阶邻接导数,(1,α)-阶伴随导数概念;应用它们导出了具Slater约束规格的集值优化问题的Benson真有效解的广义导数型Kuhn-Tucker最优性条件。     

Scalarization and Stability in Vector Optimization

A class of scalarizations of vector optimization problems is studied in order to characterize weakly efficient, efficient, and properly efficient points of a nonconvex vector problem. A parallelism is established between the different solutions of the scalarized problem and the various efficient frontiers. In particular, properly efficient points correspond to stable solutions with respect to suitable perturbations of the feasible set.     

New Generalized Convexity Notion for Set-Valued Maps and Application to Vector Optimization

In this paper, we introduce a new generalized convexity notion for set-valued maps, called ic-cone-convexlikeness, and use it as the main tool to derive an alternative theorem and necessary conditions for efficient, weakly efficient, and Benson properly efficient solutions of the problem of minimizing a set-valued map subject to set-valued constraints. Our results are valid for a class of optimization problems broader than that of the problems considered in Refs. 1--6 and generalize the corresponding results of these references.Communicated by H. P. BensonThe author thanks the anonymous referees for their remarks.     

求解广义鞍点问题的混合并行迭代法(英文)

为了在高性能计算机上求解广义鞍点问题,对于合适的系数矩阵,本文提出混合并行迭代法及其加速形式.并详细讨论了新方法的收敛性.     

Scalarization for characterization of approximate strong/weak/proper efficiency in multi-objective optimization

In this article, approximate solutions of multi-objective optimization problems are analysed. The notion of approximate solution suggested by Kutateladze is dealt with, and, utilizing different scalarization approaches, some necessary and sufficient conditions for ?-(strong, weak, proper) efficiency are provided. Almost all of the provided results are established without any convexity assumption.     

SEPARABLE CONDITIONS AND SCALARIZATION OF BENSON PROPER EFFICIENCY

Under the assumption that the ordering cone has a nonempty interior and is separable （or the feasible set has a nonempty interior and is separable）, we give scalarization theorems on Benson proper effciency. Applying the results to vector optimization problems with nearly cone-subconvexlike set-valued maps, we obtain scalarization theorems and Lagrange multiplier theorems for Benson proper effcient solutions.