一类大规模二次规划问题的可行下降分解算法

本文对一类大规模二次规划问题，提出了矩阵剖分的概念和方法，并将问题转化为求解一系列容易求解的小规模二次规划子问题．另外，通过施加某些约束机制，使子问题所产生的迭代点均为可行下降点．在通常的假定下，证明算法具有全局收敛性，大量数值实验表明，本文所提出的新算法是有效的。     

The Minimum Number of Basic Feasible Solutions to a Transport Problem

In this paper, combinatorial arguments are used to derive a lower bound to the number of basic feasible solutions of a transport problem. A separate argument is given for degenerate and non-degenerate systems, and an example which attains the lower bound is given for each type.     

求基可行解一种概率意义下的多项式算法

本文对求线性规划问题的基可行解，给出一种改型算法，证明它对m个约束、n个变量的问题，当n≥2m时，为使求得一个基可行解的概率大于0．98，对m>24，所需迭代次数不超过（m＋3），而对m≥76，迭代次数已不超过（m＋1）．     

二层规划可行解的存在性

二层规划通常是用两个最优化问题来描述，其中第一个问题(上层问题)的约束集部分受限于第二个问题(下层问题)的最优响应。可行解的存在性是二层规划问题中一个基本而重要的研究内容, 该文借助于下层目标函数的Clarke'次微分映射的w伪单调性，着重讨论了这一问题。     

Feasible direction method for large-scale nonconvex programs: Decomposition approach

In this paper, we propose a feasible-direction method for large-scale nonconvex programs, where the gradient projection on a linear subspace defined by the active constraints of the original problem is determined by dual decomposition. Results are extended for dynamical problems which include distributed delays and constraints both in state and control variables. The approach is compared with other feasible-direction approaches, and the method is applied to a power generation problem. Some computational results are included.This work was supported by the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brasilia, Brasil, and by the Fundaçao de Amparo a Pesquisa do Estado de Sao Paulo, Sao Paulo, Brazil.On leave from UNICAMP, Campinas, Brazil.     

线性规划求基可行解的一种方法

本文通过增加一个特殊约束，贯彻对偶单纯形法检验数全非正的思想，迭代求优；然后再去掉该约束，结果却可得到一个基可行解。上述过程经简化处理后，增减约束可以不必出现，它仅使单纯形表矩阵增加几次初等变换而已，足见其方法之简捷及有效性。     

线性规划问题退化最优基可行解的性质

本通过分析两用阶段法求解线性规划初始可行解的一个例子,归纳了线性规划问题退化的最优基可行解的性质,包括同一退化最优基可行解不同表示,有无穷多最优解的表示。     

图的最大二等分问题的低秩可行方向算法

基于图的最大二等分问题的半定规划松弛模型,利用矩阵的低秩分解技巧,给出了该问题的半定规划松弛的一种低秩可行方向算法.在一定的条件下,证明了算法的收敛性.结合0.699随机扰动方法得到原问题的近似最优解.数值实验表明该方法能有效地求解图的最大二等分问题.     

多目标交互可行方向法

对于多目标非线性规划问题，本文借助修正Zoutendijk法的可行方向思想，利用ε－约束问题的K－T乘子和决策者提供的权衡比产生变形标量化问题的可行下降方向，逐步求得决策者满意的有效解．     

非线性最优化一个可行序列等式约束二次规划算法

本文针对非线性不等式约束优化问题,提出了一个新的可行序列等式约束二次规划算法．在每次迭代中,该算法只需求解三个相同规模且仅含等式约束的二次规划(必要时求解一个辅助的线性规划),因而其计算工作量较小．在一般的条件下,证明了算法具有全局收敛及超线性收敛性．数值实验表明算法是有效的．     

关于群表示的分解矩阵和Cartan矩阵的两个结论

讨论了群表示中关于Cartan矩阵,Brauer特征等的性质,得到了一些结论,由这些结论,引进了所谓高度的一类概念,利用这一类概念证明了群表示论中关于分解矩阵和Cartan矩阵的两个结论.     

An Algorithm for the Modular Decomposition of Hypergraphs

We propose an O(n⁴) algorithm to build the modular decomposition tree of hypergraphs of dimension three and show how this algorithm can be generalized to compute in O(n^{3k − 5}) time the decomposition of hypergraphs of any fixed dimension k.     

A variable dimension algorithm with the Dantzig-Wolfe decomposition for structured stationary point problems

Given a set ofR ⁿ and a functionf from intoR ⁿ we consider a problem of finding a pointx ^* in such that(x–x ^*) ^t f(x ^*)0 holds for every pointx in. This problem is called the stationary point problem and the pointx ^* is called a stationary point. We present a variable dimension algorithm for solving the stationary point problem with an affine functionf on a polytope defined by constraints of linear equations and inequalities. We propose a system of equations whose solution set contains a piecewise linear path connecting a trivial starting point in with a stationary point. The path can be followed by solving a series of linear programs which inherit the structure of constraints of. The linear programs are solved efficiently with the Dantzig-Wolfe decomposition method by exploiting fully the structure.Part of this research was carried out when the first author was supported by the Center for Economic Research, Tilburg University, The Netherlands and the third author was supported by the Alexander von Humboldt-Foundation, Federal Republic of Germany.     

多目标非线性规划的可行方向交互算法

本文提出一个求解多目标非线性规划问题的交互规划算法．在每一轮迭代中,此法仅要求决策者提供目标间权衡比的局部信息．算法中的可行方向是基于求解非线性规划问题的Topkis－Veinott法构千的．我们证明,在一定条件下,此算法收敛于问题的有效解．     

一个矩阵分解算法的推广及应用

对样本相关系数矩阵等行和分解算法作了简化和推广,使算法不仅可以应用在基于正态总体非独立样本的假设检验问题,也可以有效地运用在最优化算法中牛顿法等与二次函数极小化有关的问题上.     

基于区域分解的CRS算法

本文针对带有盒子约束的非线性规划问题提出一种算法，该算法把解空间分成几个区域，根据每个区域上解的信息定义其选择概率，再根据轮盘赌选择法选择某个区域，在选择的区域上进行CRS（Control Random Search）算法操作。该方法能够缩小搜索空间，从而提高算法的搜索能力及算法的收敛速度，特别是在算法的后期效果更加明显。最后把提出的算法应用到两个典型的函数优化问题中，数值结果表明，算法是可行的、有效的。     

Dantzig-Wolfe Reformulation for the Network Pricing Problem with Connected Toll Arcs

This paper considers a pricing problem on a network with connected toll arcs and proposes a Dantzig-Wolfe reformulation for it. The model is solved with column generation and the gap between the optimal integer value and the linear relaxation optimal value is shown to be at least as good as the one from the mixed-integer formulation proposed in the literature. Numerical results on different sets of instances are reported, showing that in many cases the proposed model performs strictly better.     

A Generalized Global Cartan Decomposition: A Basic Example

Suppose G ₁ ?  G are complex linear simple Lie groups. Let  ₁ ?  be the corresponding pair of Lie algebras. For the Killing-orthogonal  of  ₁ in  we have a vector space direct sum  =  ₁⊕ , which generalizes the classical Cartan decomposition on the Lie algebras level. In this article we study the corresponding problem of a ‘generalized global Cartan decomposition’ on the Lie groups level for the pair of groups ( G , G ₁) = (SL (4,?),Sp (2,?)); here  =  (4,?),  ₁ =  (2,?), and  = {X ?  | X ^? = X}, where X? X ^? is the symplectic involution. We prove that G  =  G ₁exp  ∪ i G ₁exp . The key point of the proof is to study in detail the set exp ; and for that purpose we introduce the J-twisted Pfaffian of size 2n defined on the set of all 2n × 2n matrices X satisfying X ^? = X, which is here a natural counterpart of the standard Pfaffian.     

不等式约束优化一个超线性收敛的可行内点型算法

本文针对非线性不等式约束优化问题,提出了-个可行内点型算法.在每次迭代中,基于积极约束集策略,该算法只需求解三个线性方程组,因而其计算工作量较小.在-般的条件下,证明了算法具有全局收敛及超线性收敛性.