二层不变凸规划的性质

在G^ateaux可微和不变凸假设下,给出了二层广义凸规划的凸性,推广了二层规划的若干结果.     

一类二层凸规划的对偶二层规划

本文讨论上层目标函数以下层子系统目标函数的最优值作为反馈的一类二层凸规划的对偶规划问题 ,在构成函数满足凸连续可微等条件的假设下 ,建立了二层凸规划的 Lagrange对偶二层规划 ,并证明了基本对偶定理 .     

凸二次-线性双层规划的共轭对偶及其性质

研究具有一般形式的凸二次-线性双层规划问题。讨论了这类双层规划问题的DC规划等价形式,利用DC规划共轭对偶理论,提出了凸二次-线性双层规划的共轭对偶规划,并给出相应的对偶性质。     

二层广义凸规划及其性质

讨论了二层规划的性质 ,在一些凸性和广义凸性假设下 ,讨论了下层极值函数和上层目标函数的凸性、拟凸性和连续性性质 ,获得了五个定理 ,并予以证明 .     

二层凸规划的基本性质

本文研究了一类抛述二层决策问题的二层数学规划模型，在一定条件下讨论了下层极值函数和上层复合目标函数的凸性和连续性，给出了二层决策问题优决策的存在条件。     

凸规划的新算法

对一般凸目标函数和一般凸集约束的凸规划问题新解法进行探讨,它是线性规划一种新算法的扩展和改进,此算法的基本思想是在规划问题的可行域中由所建－的一个切割面到另一个切割面的不断推进来求取最优的。文章对目标函数是二次的且约束是一般凸集和二次目标函数且约束是线性的情形,给出了更简单的算法。     

一类二层规划的上图收敛性

以下层规划的最优值作为响应反馈到上层的一类二层规划问题，可以放宽要求下层规划具有唯一解的限制．本文旨在讨论这类二层规划序列的上图收敛性，从而对近似求解这类问题提供了一定的理论依据．     

一些约束规划问题的近似全局最优解

首先将一个具有多个约束的规划问题转化为一个只有一个约束的规划问题,然后通过利用这个单约束的规划问题,对原来的多约束规划问题提出了一些凸化、凹化的方法,这样这些多约束的规划问题可以被转化为一些凹规划、反凸规划问题．最后,还证明了得到的凹规划和反凸规划的全局最优解就是原问题的近似全局最优解．     

关于宏观经济的凸二次规划模型

本文运用凸二次规划理论，通过引入价格变量建立观经济的凸二次规划模型．并指出在社会主义市场经济中企业、产业、国家可以同时达到最优．     

凸二次交叉规划的等价形式

利用参数规划逆问题考虑凸二次交叉规划与多目标规划的关系 ,把交叉规划转变为同变量规划组 ,再把同变量规划组变为多目标规划 ,证明了凸二次交叉规划的均衡解与多目标规划的最优解的关系。     

Exact Penalty Functions for Convex Bilevel Programming Problems

In this paper, we propose a new constraint qualification for convex bilevel programming problems. Under this constraint qualification, a locally and globally exact penalty function of order 1 for a single-level reformulation of convex bilevel programming problems is given without requiring the linear independence condition and the strict complementarity condition to hold in the lower-level problem. Based on these results, locally and globally exact penalty functions for two other single-level reformulations of convex bilevel programming problems can be obtained. Furthermore, sufficient conditions for partial calmness to hold in some single-level reformulations of convex bilevel programming problems can be given.     

A neural network for solving a convex quadratic bilevel programming problem

A neural network is proposed for solving a convex quadratic bilevel programming problem. Based on Lyapunov and LaSalle theories, we prove strictly an important theoretical result that, for an arbitrary initial point, the trajectory of the proposed network does converge to the equilibrium, which corresponds to the optimal solution of a convex quadratic bilevel programming problem. Numerical simulation results show that the proposed neural network is feasible and efficient for a convex quadratic bilevel programming problem.     

一类值型双层凸规划的Johri一般对偶

本文首先给出一类特殊的值型凸二次双层规划一其下层子规划只含有线性约束(简记为VBCP)；然后证明了一般形式的VBCP可以等价变换为非增值型凸二次双层规划的形式；最后给出该类双层规划VBCP的Johri对偶规划及其对偶性质．     

A trust region algorithm for solving bilevel programming problems

In this paper, we present a new trust region algorithm for a nonlinear bilevel programming problem by solving a series of its linear or quadratic approximation subproblems. For the nonlinear bilevel programming problem in which the lower level programming problem is a strongly convex programming problem with linear constraints, we show that each accumulation point of the iterative sequence produced by this algorithm is a stationary point of the bilevel programming problem.     

Descent approaches for quadratic bilevel programming

The bilevel programming problem involves two optimization problems where the data of the first one is implicitly determined by the solution of the second. In this paper, we introduce two descent methods for a special instance of bilevel programs where the inner problem is strictly convex quadratic. The first algorithm is based on pivot steps and may not guarantee local optimality. A modified steepest descent algorithm is presented to overcome this drawback. New rules for computing exact stepsizes are introduced and a hybrid approach that combines both strategies is discussed. It is proved that checking local optimality in bilevel programming is a NP-hard problem.Support of this work has been provided by INIC (Portugal) under Contract 89/EXA/5, by FCAR (Québec), and by NSERC and DND-ARP (Canada).     

Methods of Chebyshev points of convex sets and their applications

Chebyshev points of bounded convex sets, search algorithms for them, and various applications to convex programming are considered for simple approximations of reachable sets, optimal control, global optimization of additive functions on convex polyhedra, and integer programming. The problem of searching for Chebyshev points in multicriteria models of development and operation of electric power systems is considered.     

带有极值函数的多目标双层规划问题的对偶

For a multiobjective bilevel programming problem(P) with an extremal-value function,its dual problem is constructed by using the Fenchel-Moreau conjugate of the functions involved.Under some convexity and monotonicity assumptions,the weak and strong duality assertions are obtained.     

二(双)层规划综述

二(双)层规划是研究二层决策的递阶优化问题.其理论、方法和应用在过去的30多年取得了很大的发展.本文对二层规划问题的基本概念、性质和算法作了综述,并且对下层规划问题的解不唯一的情况也作了介绍,最后还给出了几种常见的二层规划模型.     

Weak and strong stationarity in generalized bilevel programming and bilevel optimal control

In this article, we consider a general bilevel programming problem in reflexive Banach spaces with a convex lower level problem. In order to derive necessary optimality conditions for the bilevel problem, it is transferred to a mathematical program with complementarity constraints (MPCC). We introduce a notion of weak stationarity and exploit the concept of strong stationarity for MPCCs in reflexive Banach spaces, recently developed by the second author, and we apply these concepts to the reformulated bilevel programming problem. Constraint qualifications are presented, which ensure that local optimal solutions satisfy the weak and strong stationarity conditions. Finally, we discuss a certain bilevel optimal control problem by means of the developed theory. Its weak and strong stationarity conditions of Pontryagin-type and some controllability assumptions ensuring strong stationarity of any local optimal solution are presented.