集值映射向量优化问题的锥弱有效解的镇定性和稳定性

本文研究了集值映射向量优化问题的锥弱有效解的镇定性和稳定性,我们引进了集值映射向量优化问题的镇定性和稳定性的定义,并证明了集值映射问题优化问题的镇定性和稳定性的一些主要定理。     

集值映射向量优化问题的精确罚函数镇定性和稳定性（英文）

精确罚函数理论中镇定性和稳定性是非常重要的条件,因为它们是判断精确罚函数的充分必要条件,本文基于集值映射向量优化问题的锥弱有效解,提出它们的镇定性和稳定性概念,并讨论它们的性质,证明在这些概念下集值向量优化问题的罚函数精确性.     

对称集值向量拟均衡问题解集的稳定性

本文研究了对称集值向量拟均衡问题解集的稳定性.证明了在约束映射满足一定连续性与目标映射是锥-恰当拟凸的集值映射条件下,对称集值向量拟均衡问题的解集是稳定的,还证明了每个对称集值向量拟均衡问题的解集至少存在一个本质连通区.     

扰动集值优化问题超有效点集的次微分稳定性

在锥序Banach向量空间引入了集值映射在超有效意下的次微分(次梯度);在一定的条件下,证明次微分(次梯度)的存在性;得到了序扰动、双扰动集值优化问题超有效点集在次微分意义下的稳定性．     

方向导数和广义锥-预不变凸集值优化问题

讨论拓扑向量空间中无约束集值优化问题的最优性条件问题.利用集值映射的Dini方向导数,在广义锥-预不变凸性条件下,建立了集值优化问题关于弱极小元和强极小元的最优性充分必要条件.     

向量均衡问题强有效解的稳定性

在可行集扰动而向量值映射不扰动、可行集与向量值映射均扰动、可行集扰动而集值映射不扰动以及可行集与集值映射均扰动四种情况下,分别讨论了向量均衡问题强有效解的稳定性.     

集值向量优化的二阶最优性条件

对集值映射引入了高阶Clarke导数,给出了判别集值向量优化所有效性的二阶Kuhn-Tucker条件,并且,借助于集值映射的强(弱)伪凸性给出了一个弱有效解的充分条件.     

一类集值映射向量优化问题的ε-有效解

集值映射向量优化问题是最优化理论中的一个重要方向.在集值映射为生成锥内部-锥一类凸(简记为ic-锥类凸)的假设条件下,利用择一定理,给出了集值映射向量优化问题ε-弱有效解和ε-有效解的最优性条件和ε-Lagrange乘子定理,是弱有效解和有效解相应结果的推广.     

集值向量优化的二阶量优性条件

对集值映射引入了高阶Clarke导数,给出了判别集值向量优化所有效性的二阶Kuhn-Tucker条件,并且,借助于集值映射的强（弱）伪凸性给出了一个弱有效解的充分条件。     

广义强向量拟均衡问题组解的存在性

本文研究了一类集值广义强向量拟均衡问题组解的存在性问题.利用集值映射的自然拟C-凸性和集值映射的下(-C)-连续性的定义和Kakutani-Fan-Glicksberg不动点定理,在不要求锥C的对偶锥C~*具有弱*紧基的情况下,建立了该类集值广义强向量拟均衡问题组解的存在性定理.所得结果推广了该领域的相关结果.     

Optimality Conditions for Vector Optimization Problems

In this paper, some necessary and sufficient optimality conditions for the weakly efficient solutions of vector optimization problems (VOP) with finite equality and inequality constraints are shown by using two kinds of constraints qualifications in terms of the MP subdifferential due to Ye. A partial calmness and a penalized problem for the (VOP) are introduced and then the equivalence between the weakly efficient solution of the (VOP) and the local minimum solution of its penalized problem is proved under the assumption of partial calmness. This work was supported by the National Natural Science Foundation of China (10671135), the Specialized Research Fund for the Doctoral Program of Higher Education (20060610005) and the National Natural Science Foundation of Sichuan Province (07ZA123). The authors thank Professor P.M. Pardalos and the referees for comments and suggestions.     

多目标规划的弱镇定性、弱稳定性及其精确罚函数

本文将 Rosenberg 在文[1]中定义的单目标规划的镇定性、稳定性概念推广到多目标的情形,讨论多目标规划问题(VP)(?)f(x)s.t.g_k(x)≤0,k∈K_1,h_k(x)=0,k∈K_2的弱镇定性、弱稳定性、局部弱稳定性、一致局部弱稳定性,以及罚函数问题     

Quantitative Stability of a Generalized Equation

The paper is devoted to the study of several stability properties (such as Aubin/Lipschitz-like property, calmness and isolated calmness) of a special non-monotone generalized equation. The theoretical results are applied in the theory of non-regular electrical circuits involving electronic devices like ideal diode, practical diode, and diode alternating current.     

Calmness of efficient solution maps in parametric vector optimization

The paper is concerned with the stability theory of the efficient solution map of a parametric vector optimization problem. Utilizing the advanced tools of modern variational analysis and generalized differentiation, we study the calmness of the efficient solution map. More explicitly, new sufficient conditions in terms of the Fréchet and limiting coderivatives of parametric multifunctions for this efficient solution map to have the calmness at a given point in its graph are established by employing the approach of implicit multifunctions. Examples are also provided for analyzing and illustrating the results obtained.     

Optimization methods and stability of inclusions in Banach spaces

Our paper deals with the interrelation of optimization methods and Lipschitz stability of multifunctions in arbitrary Banach spaces. Roughly speaking, we show that linear convergence of several first order methods and Lipschitz stability mean the same. Particularly, we characterize calmness and the Aubin property by uniformly (with respect to certain starting points) linear convergence of descent methods and approximate projection methods. So we obtain, e.g., solution methods (for solving equations or variational problems) which require calmness only. The relations of these methods to several known basic algorithms are discussed, and errors in the subroutines as well as deformations of the given mappings are permitted. We also recall how such deformations are related to standard algorithms like barrier, penalty or regularization methods in optimization.     

On second-order optimality conditions for continuously Fréchet differentiable vector optimization problems

ABSTRACT

In this paper, we study a vector optimization problem (VOP) with both inequality and equality constraints. We suppose that the functions involved are Fréchet differentiable and their Fréchet derivatives are continuous or stable at the point of study. By virtue of a second-order constraint qualification of Abadie type, we provide second-order Karush–Kuhn–Tucker type necessary optimality conditions for the VOP. Moreover, we also obtain second-order sufficient optimality conditions for a kind of strict local efficiency. Both the necessary conditions and the sufficient conditions are shown in equivalent pairs of primal and dual formulations by using theorems of the alternative for the VOP.     

On constraint qualifications in terms of approximate Jacobians for nonsmooth continuous optimization problems

Constraint qualifications in terms of approximate Jacobians are investigated for a nonsmooth constrained optimization problem, in which the involved functions are continuous but not necessarily locally Lipschitz. New constraint qualifications in terms of approximate Jacobians, weaker than the generalized Robinson constraint qualification (GRCQ) in Jeyakumar and Yen [V. Jeyakumar, N.D. Yen, Solution stability of nonsmooth continuous systems with applications to cone-constrained optimization, SIAM J. Optim. 14 5 (2004) 1106-1127], are introduced and some examples are provided to show the utility of constrained qualifications introduced. Since the calmness condition is regarded as the basic condition for optimality conditions, the relationships between the constraint qualifications proposed and the calmness of solution mapping are also studied.     

Calmness of constraint systems with applications

The paper is devoted to the analysis of the calmness property for constraint set mappings. After some general characterizations, specific results are obtained for various types of constraints, e.g., one single nonsmooth inequality, differentiable constraints modeled by polyhedral sets, finitely and infinitely many differentiable inequalities. The obtained conditions enable the detection of calmness in a number of situations, where the standard criteria (via polyhedrality or the Aubin property) do not work. Their application in the framework of generalized differential calculus is explained and illustrated by examples associated with optimization and stability issues in connection with nonlinear complementarity problems or continuity of the value-at-risk. This research was supported by the DFG Research center Matheon Mathematics for key technologies in Berlin Support by grant IAA1030405 of the Grant Agency of the Academy of Sciences of the Czech Republic is acknowledged     

Strong calmness of perturbed KKT system for a class of conic programming with degenerate solutions

ABSTRACT

This paper is concerned with the strong calmness of the KKT solution mapping for a class of canonically perturbed conic programming, which plays a central role in achieving fast convergence under situations when the Lagrange multiplier associated to a solution of these conic optimization problems is not unique. We show that the strong calmness of the KKT solution mapping is equivalent to a local error bound for the solutions to the perturbed KKT system, and is also equivalent to the pseudo-isolated calmness of the stationary point mapping along with the calmness of the multiplier set mapping at the corresponding reference point. Sufficient conditions are also provided for the strong calmness by establishing the pseudo-isolated calmness of the stationary point mapping in terms of the noncriticality of the associated multiplier, and the calmness of the multiplier set mapping in terms of a relative interior condition for the multiplier set. These results cover and extend the existing ones in Hager and Gowda [Stability in the presence of degeneracy and error estimation. Math Program. 1999;85:181–192]; Izmailov and Solodov [Stabilized SQP revisited. Math Program. 2012;133:93–120] for nonlinear programming and in Cui et al. [On the asymptotic superlinear convergence of the augmented Lagrangian method for semidefinite programming with multiple solutions. 2016, arXiv: 1610.00875v1]; Zhang and Zhang [Critical multipliers in semidefinite programming. 2018, arXiv: 1801.02218v1] for semidefinite programming.     

A hybrid approach for finding efficient solutions in vector optimization with SOS-convex polynomials

This paper aims to find efficient solutions to a vector optimization problem (VOP) with SOS-convex polynomials. A hybrid scalarization method is used to transform (VOP) into a scalar one. A strong duality result, between the proposed scalar problem and its relaxation dual problem, is established, under certain regularity condition. Then, an optimal solution to the proposed scalar problem can be found by solving its associated semidefinite programming problem. Consequently, we observe that finding efficient solutions to (VOP) can be achieved.