一类n阶方程Robin问题的存在性定理和对解的估计

在文献[1]中,Kelley利用上、下解证明了一类n阶方程Dirichlet问题解的存在性,Howes讨论了这类问题解的零阶近似。而本文先利用上、下解证明了这类问题中的Robin问题的解的存在性,再利用微分不等式理论研究了奇摄动Robin问题的包括边界层在内的解的任意阶近似。     

线性规划问题非唯一最优解的存在条件和解集结构

设线性规划问题为其中A是秩为m的m×n矩阵,m相似文献   

矩阵计策的支撑解系

令[aij]n×n是二人零和对策的支付矩阵.局中人1可用其"计策"得到最大支付a＝max{aij|1≤i≤n,1≤j≤n},然而,一个开放问题是如何找到全体计策解,本文首先引进计策解系的一种特殊类型--支撑解系.然后研究支撑解系的特征、性质、代数结构.最后给出寻找全体基本支撑解系的一个算法.     

影子价格与企业管理决策

本文利用线性规划与非线性规划模型，讨论了目标函数增量，影子价格及相应的常数项增量的特征区间之间的关系，从理论上对文[1]、[2]、[3]中的问题作出了解释。我们还给出了线性规划与非线性规划发生悖论的充要条件，对文[5]、[7]中的结果进行了推广。     

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）．     

线性规划标准型和整数线性规划最优解的两个注记

本文研究线性规划标准型的基本假设所蕴含的一些性质,并探讨整数线性规划最优解和其松弛问题最优解的关系.首先,分别讨论四种情形下线性规划最优解的性质,即无约束线性规划问题、仅有非负约束的线性规划问题、仅有等式约束的线性规划问题,以及标准线性规划问题系数矩阵的列向量有为零的情形等.然后,构造两族二维整数线性规划,其松弛问题的最优解与其(整数)最优解"相距甚远".     

一类n阶微分方程零解的稳定性

n 阶变系数非线性微分方程零解的稳定性一般说来是比较困难的问题。文献[4]讨论了一类变系数线性微分方程零解稳定性。本文讨论非线性情形。考虑 n 阶非线性微分方程     

一类微分差分方程的周期解

泛函微分方程周期解的存在性问题是重要而困难的。文[1—3]分别用Kaplan—Yorke方法研究了含一个滞量的微分差分方程的周期解问题。文[4]用Kaplan-Yorke方法研究了含二个滞量的微分差分方程周期解的存在性问题。本文研究微分差分方程     

关于微分方程组解的m-非允许分量

在本文里，我们给出了微分方程组解的非允许分量之定义，探讨了一类微分方程组解的m-非允许分量的存在性问题，得到了几个结果。它是文[9]的进—步讨论．     

关于whc168精确解的一个上界

Whc16 8　一堆书放入n个抽屉 (允许有空抽屉 ) ,为了使任意两个抽屉里书的数目之差不同 ,问至少要有多少本书 ?2 0 0 0年以来 ,本刊文 [1]～文 [7]相继对这一问题进行了探讨 ,分别给出n (n≥ 3)个抽屉里书的总数Sn 的若干下界 ,其中文 [7]的结果最强 ,文 [1]的结果最简 .文 [1]给出的结果为 :Sn≥ n3 -n6 (1)为探讨Whc16 8的精确解 ,文 [7]给出了可装书数列的概念 :定义　若数列 {an}的任意两项之差均不相同 ,则称数列 {an}是可装书数列 .(注 :笔者认为上述定义中加上条件“an∈N”较好 )并证明了下述结果 :命题　任意公比是大于 1的整数…     

解聯立方程的差分方程法

<正> 一. 引 聯立一次方程的求解早就不是一個理論問題,而是一個改進計算技術的問題.問題在如何組織計算使計算機械化從而節省工作量. 給定充分多始值後,線性差分方程是很容易解的.在本文內,我們把特種的及一般的聯立一次方程組的解看作線性差分方程滿足某種邊值的解,從而推求出求聯立一次方程組的準確解的一種簡單的機械的列表計算方法。     

一类系数为梯形模糊数的两层线性规划

讨论了一类系数为梯形模糊数的两层线性规划问题,首先是利用模糊结构元理论将梯形模糊数去模糊化,将其转化成常规的两层线性问题,并验证其去模糊化后的常规的两层线性规划的最优解与系数为梯形模糊数的两层线性规划问题的最优解一致,并给出具体的算法,数例进行验证.     

The Simplex and the Dual Method for Quadratic Programming

The paper presents a straightforward generalization of the Simplex and the dual method for linear programming to the case of convex quadratic programming. The two algorithms, called the Simplex and the dual method for quadratic programming, are applicable when the matrix of the quadratic part of the objective function, in case this function is to be maximized, is negative definite, negative semi-definite or zero; in the last case the two methods are equivalent to an application of the similar methods for linear programming. The paper gives an exposition of the methods as well as examples and interpretations. The relations with linear programming methods are considered and some starting procedures in case no initial feasible solution is available are presented.     

Fixing variables and generating classical cutting planes when using an interior point branch and cut method to solve integer programming problems

Branch and cut methods for integer programming problems solve a sequence of linear programming problems. Traditionally, these linear programming relaxations have been solved using the simplex method. The reduced costs available at the optimal solution to a relaxation may make it possible to fix variables at zero or one. If the solution to a relaxation is fractional, additional constraints can be generated which cut off the solution to the relaxation, but donot cut off any feasible integer points. Gomory cutting planes and other classes of cutting planes are generated from the final tableau. In this paper, we consider using an interior point method to solve the linear programming relaxations. We show that it is still possible to generate Gomory cuts and other cuts without having to recreate a tableau, and we also show how variables can be fixed without using the optimal reduced costs. The procedures we develop do not require that the current relaxation be solved to optimality; this is useful for an interior point method because early termination of the current relaxation results in an improved starting point for the next relaxation.     

An Algorithm for Solving Multicriterion Linear Programming Problems with Examples

The purpose of this paper is to develop a useful technique for solving linear programmes involving more than one objective function. Motivation for solving multicriterion linear programmes is given along with the inherent difficulty associated with obtaining a satisfactory solution set. By applying a linear programming approach for the solution of two person–zero sum games with mixed strategies, it is shown that a linear optimization problem with multiple objective functions can be formulated in this fashion in order to obtain a solution set satisfying all the requirements for an efficient solution of the problem. The solution method is then refined to take into account disparities between the magnitude of the values generated by each of the objective functions and solution preferences as determined by a decision-maker. A summary of the technique is then given along with several examples in order to demonstrate its applicability.     

目标系数模糊型模糊关系线性规划

提出了目标系数模糊型模糊关系线性规划问题,这是传统模糊关系线性规划的扩展.以三角模糊数为例,基于它的一种排序方法给出了求解该类规划的一个算法.最后,为了说明算法的有效性给出了两个数值例子.     

含交易费用的证券组合投资模型的满意解

在证券组合投资过程中,忽略交易费用会导致非有效的证券组合投资,本文提出了一个考虑交易费用的证券组合投资的区间数线性规划模型,通过引入区间数线性规划问题中的目标函数优化水平参数λ和约束条件满足水平参数η将目标函数和约束条件均为区间数的区间数线性规划模型转化为确定型的一般线性规划模型,进而求得相应于优化水平λ和满足水平η的满意解.     

On the convergence of cross decomposition

Cross decomposition is a recent method for mixed integer programming problems, exploiting simultaneously both the primal and the dual structure of the problem, thus combining the advantages of Dantzig—Wolfe decomposition and Benders decomposition. Finite convergence of the algorithm equipped with some simple convergence tests has been proved. Stronger convergence tests have been proposed, but not shown to yield finite convergence.In this paper cross decomposition is generalized and applied to linear programming problems, mixed integer programming problems and nonlinear programming problems (with and without linear parts). Using the stronger convergence tests finite exact convergence is shown in the first cases. Unbounded cases are discussed and also included in the convergence tests. The behaviour of the algorithm when parts of the constraint matrix are zero is also discussed. The cross decomposition procedure is generalized (by using generalized Benders decomposition) in order to enable the solution of nonlinear programming problems.     

Control and Game-Theoretical Treatment of a Cost-Security Model for Disarmament

In this paper a time-discrete dynamic model for the process of disarmament is investigated. The state variables of the system are costs and security values. We assume that the costs can be controlled, and we aim at reducing the costs to zero and achieving non-negative security values after a finite number of time steps. In the case where the opponents behave cooperatively this leads to the solution of a linear programming problem. If the opponents behave non-cooperatively, then a Nash equilibrium has to be determined under linear constraints. © 1997 by B. G. Teubner Stuttgart–John Wiley & Sons Ltd. Math. Meth. Appl. Sci., Vol. 20, 653–666 (1997).     

一种基于区间数的证券组合投资模型与求解

提出了区间数的相对左偏度的定义.利用区间数的相对左偏度作为区间数下表达证券风险损失率的一种补充,能合理地反映风险损失率与预期收益率之间的相关关系.建立了一种新的证券组合投资区间数规划模型,将区间数规划模型转化为参数线性规划问题求解,使证券组合投资决策分析更加具有柔性.最后通过实例分析了该模型的应用价值.