巧用线性规划解题三例

由于线性规划沟通了数与形之间的有机联系,这就为把线性规划知识演化成线性规划方法提供了肥沃的土壤,也为线性规划方法展示了广阔的应用前景。因此,对于线性规划来说,不能只局限在线性规划问题的应用之中,还必须努力跨越数学分支间的“鸿沟”,变通“线性规划”的使用范围,扩大用“线性规划”来解题的效益,使“线性规划”在横向联系中求发...     

一类系数为梯形模糊数的两层多随从线性规划模型

针对一类系数为梯形模糊数的两层多随从线性规划问题,利用模糊结构元理论定义了模糊结构元加权序,证明了一类系数为梯形模糊数的两层多随从线性规划问题的最优解等价于两层多随从线性规划问题的最优解.根据线性规划的对偶定理和互补松弛性质,得到了两层多随从线性规划模型的最优化条件.最后,利用两层多随从线性规划模型的最优化条件,设计了求解一类系数为梯形模糊数的两层多随从线性规划问题的算法,并通过算例验证了该方法的可行性和合理性.     

2008高考线性规划创新题透视

综观2008年的全国各地高考试题,几乎都涉及了线性规划,而且题型也越来越开放,从单一的、静态的线性规划发展到较全面的、动态的线性规划.本文对2008高考卷中的线性规划创新题--动态线性规划问题进行剖析,以期对大家有所启发.……     

互补基解性质的应用研究

对线性规划互补基解性质进行了研究,得到了由线性规划问题最优基对应的单纯形表直接获得对偶线性规划问题最优基对应的单纯形表的一个有效方法,给出了应用实例.     

求解线性规划的一种单纯形矩阵法

线性规划的单纯形法一直是运筹学教学中的难点,是求解线性规划的一种重要方法.通过实例从代数角度探讨了单纯形法的迭代思想,提出了用单纯形矩阵求解线性规划的方法.同传统的单纯形表计算比较而言,此方法操作简单,不易出错,为线性规划的求解提供了一种行之有效的方法。     

线性规划解法的发展概况

这个数学问题是 G、B、Dantzig 在1947年提出来的。同时他又给出了一个解法,就是有名的单纯形方法。卅多年来,线性规划理论得到很大的发展。关于线性规划的论文数以万计,包括研究各种特殊类型的线性规划问题、线性规划的各种应用以及线性规划的解法研究等。特别是解法,多年来,一直是线性规划研究的重要方向。     

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".     

含直觉模糊弹性约束的多目标模糊线性规划求解

基于模糊结构元方法构建并讨论了一类含有直觉模糊弹性约束的多目标模糊线性规划问题.通过引入模糊数的加权特征数,定义了一种序关系并拓展了Verdegay的模糊线性规划方法,将上述多目标模糊线性规划问题转化成两个等价含参数约束条件的清晰多目标线性规划模型,并应用一种线性加权函数法给出了此类线性规划模型的对比最优可行解.最后通过一个数值实例来说明此类问题的一般求解方法.     

用线性规划处理含|Ax+By+C|结构单元的数学问题

线性规划是数学规划理论中理论较完整、方法较成熟、应用较广泛的一个分支.线性规划思想充分体现了数学的工具性、应用性.线性规划作为一种工具,不仅拓展了不等式的教育价值,有利于     

线性规划的符号跟踪算法

分析了只含一个约束条件的线性规划最优基变量的特征，将其运用到搜寻含m个约束条件的线性规划的最优基变量，从而提出了线性规划的符号跟踪算法，为线性规划求解提供了新途径。     

A partitioning and bounded variable algorithm for linear programming

An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does not introduce artificial variables. In the PBVA, a reduced linear program is formed by eliminating as many variables as there are equality constraints. A subproblem containing one ‘less than or equal to’ constraint is solved by executing the simplex method modified such that an upper bound is placed on an unbounded entering variable. The remaining constraints of the reduced problem are added to the optimal tableau of the subproblem to form an augmented tableau, which is solved by applying the dual simplex method for bounded variables. Lastly, the variables that were eliminated are restored by substitution. Differences between the PBVA and two other variants of the simplex method are identified. The PBVA is applied to solve an example problem with five decision variables, two equality constraints, and two inequality constraints. In addition, three other types of linear programming problems are solved to justify the advantages of the PBVA.     

第一阶段原有单纯形和对偶单纯形算法的计算比较

线性最优化广泛应用于经济与管理的各个领域.在线性规划问题的求解中,如果一个初始基本可行解没有直接给出,则常采用经典的两阶段法求解.对含有"≥"不等式约束的线性规划问题,讨论了第一阶段原有单纯形法和对偶单纯形法两种算法形式,并根据第一阶段问题的特点提出了改进的对偶单纯形枢轴准则.最后,通过大规模数值试验对两种算法进行计算比较,结果表明,改进后的对偶单纯形算法在计算效率上明显优于原有单纯形算法.     

En空间中张角定理及其应用

本文利用单形的体积公式,得到了n维欧氏空间Eⁿ中的张角定理,由此又证得了单形中的一组恒等式,利用这组恒等式给出了Safta猜想在Eⁿ空间中的加强形式．     

单纯形调优法的收敛性质

在非线性规划中,单纯形调优法是一种可信用的算法,然而却缺乏理论分析,本文对单纯形调优法的理论进行了一些研究,所考虑的方法类似于Spendley,Hext,Himsworth的正规单纯形调优法,但采用了不同的反映条件,其中带有某种下山门槛或具有三点下降形式,这里的基本思想是证明:上述单纯形调优法是定步长下山法的特殊情形,所以,此研究紧密联系着作者关于定步长下山法收敛定理的工作。     

A conjugate Rosen’s gradient projection method with global line search for piecewise linear concave optimization

The Kelley cutting plane method is one of the methods commonly used to optimize the dual function in the Lagrangian relaxation scheme. Usually the Kelley cutting plane method uses the simplex method as the optimization engine. It is well known that the simplex method leaves the current vertex, follows an ascending edge and stops at the nearest vertex. What would happen if one would continue the line search up to the best point instead? As a possible answer, we propose the face simplex method, which freely explores the polyhedral surface by following the Rosen’s gradient projection combined with a global line search on the whole surface. Furthermore, to avoid the zig-zagging of the gradient projection, we propose a conjugate gradient version of the face simplex method. For our preliminary numerical tests we have implemented this method in Matlab. This implementation clearly outperforms basic Matlab implementations of the simplex method. In the case of state-of-the-art simplex implementations in C or similar, our Matlab implementation is only competitive for the case of many cutting planes.     

On solving the maximum clique problem

The Maximum Clique Problem (MCP) is regarded here as the maximization of an indefinite quadratic form over the canonical simplex. For solving MCP an algorithm based upon Global Optimality Conditions (GOC) is applied. Furthermore, each step of the algorithm is analytically investigated and tested. The computational results for the proposed algorithm are compared with other Global Search approaches.     

On a construction of Lindenstrauss and Wulbert

We show that a certain construction of a Lindenstrauss space based on intersections of balls, which was done first by Lindenstrauss and Wulbert, leads to a Gurarij space (of any density character). This provides us with new simple proofs of some assertions about Gurarij spaces as well as of the following:Any compact Choquet simplex (not necessarily metrizable) is affinely homomorphic to a face of a Poulsen simplex S, i.e., a compact Choquet simplex whose extreme points are dense in all S.     

线性规划的对偶基线算法

In this paper,we studied the dual form of the basic line algorthm for linear programs.It can be easily implemented in tableau that similar to the primal/dual simplex method.Different from primal simplex method or dual simplex method,the dual basic line algorithm can keep primal feasibility and dual feasibility at the same time in a tableau,which makes it more efficient than the former ones.Principles and convergence of dual basic line algorthm were discussed.Some examplex and computational experience were given to illustrate the efficiency of our method.     

Truncations of principal geometries

We investigate the class of principal pregeometries (free simplicial geometries with spanning simplex) which form an important subclass of the class of transversal pregeometries (free simplicial geometries). We give a coordinate-free method for imbedding a transversal pregeometry on a simplex as a free simplicial pregeometry which makes use only of the set-theoretic properties of a presentation of the transversal pregeometry. We introduce the notion of an (r, k)-principal set as a generalization of principal basis and prove the collection of (r, k)-principal sets of a rank k pregeometry, if non-empty, are the bases of another pregeometry whose structure is determined. An algorithm for constructing principal sets is given. We then characterize truncations of principal geometries in terms of the existence of a principal set. We do this by erecting a given pregeometry to a free simplicial pregeometry with spanning simplex. The erection is the freest of all erections of the given pregeometry.     

Sparse solutions to random standard quadratic optimization problems

The standard quadratic optimization problem (StQP) refers to the problem of minimizing a quadratic form over the standard simplex. Such a problem arises from numerous applications and is known to be NP-hard. In this paper we focus on a special scenario of the StQP where all the elements of the data matrix Q are independently identically distributed and follow a certain distribution such as uniform or exponential distribution. We show that the probability that such a random StQP has a global optimal solution with k nonzero elements decays exponentially in k. Numerical evaluation of our theoretical finding is discussed as well.