单纯形法求解与Excel规划求解

利用单纯形法求解线性规划问题在产品品种问题、合理配料问题、开料问题等问题中有着极其广泛的应用,但整个计算过程非常繁杂,而且容易计算错误。对Excel规划求解的研究发现,利用Excel中的规划求解工具可以实现单纯形法求解线性规划的问题,大大提高了求解的速度和准确性。     

基于对分法求解线性规划问题的神经网络方法

从数值逼近的方法出发,结合对分法的思想,提出了一种新的神经网络计算模型,我们称为对分神经网络BNN(BisectNeuralNetwork)模型;给出了一种基于对分法思想的神经网络学习算法,并用于求解线性规划问题,其目的是给线性规划求解问题提供一个新方法。     

基于单纯形法和局部枚举解混合整数线性规划问题

提出了一种基于单纯形法和局部枚举求解整数线性规划问题的新方法。它通过单纯形法得到松弛问题的最优解并确定变量以及目标函数取值范围,然后基于目标函数,进行局部枚举,从而得到其整数线性规划问题的最优解,与现有方法比较,新解法简单,计算量少,尤其是对于大规模整数线性规划问题,计算量少体现地更明显。     

利用EXCEL2010求解线性规划问题

该文讨论了使用EXCEL2010求解运筹学中比较重要的线性规划特定问题的求解方法,从而大大简化了变量比较多的线性规划问题的求解方法。     

分片线性规划及应用

提出通过分片线性逼近和分片线性规划,将非线性优化问题转化为一系列的线性规划进行求解的方法。讨论了分片线性规划的性质,证明了分片线性规划问题可以通过有限次线性规划得到求解,同时,给出了分片线性规划问题局部最优解的充要条件,并基于此构造了求解分片线性规划问题的下降算法。该算法与自适应链接超平面模型相结合,成功地对离心式冷水机组的工作点进行了优化。通过优化,机组的能耗比之当前工作点有了明显的下降,表明通过分片线性规划求解非线性优化问题的有效性。     

利用EXCEL2010求解线性规划问题

该文讨论了使用EXCEL2010求解运筹学中比较重要的线性规划特定问题的求解方法，从而大大简化了变量比较多的线性规划问题的求解方法。     

Excel在求解方程式中的应用

Excel具有强大计算功能,在众多领域有着广泛的应用.针对手工求解超越方程、线性方程组、线性规划问题比较繁琐的情况,提出使用Excel求解方程式的方法.     

上下层具有合作关系的两层决策问题研究

针对两层线性规划问题解的无效性,在决策者合作情形下,利用双准则线性规划的有关技术,提出事先不需求解问题而是采用次最优解作为参考点,直接在目标集中有效满意解的方法。数值计算结果表明该方法有效可行的。     

简化线性规划模型的方法研究及实现

一般的线性规划模型都存在大量的冗余约束,这些冗余约束势必会干扰线性规划问题的求解,降低解题速度,影响解题效率。如果在求解线性规划问题之前,能够对这些冗余约束进行化简并消去,就能够提高模型中约束矩阵的稀疏度,缩小线性规划问题的规模,且在求解时能节省大量的计算机存储空间和运算时间。提出了一种新的简化线性规划模型的方法,程序实现后试验表明,该简化方法达到了预期的效果。     

成套产品下料模型及其辅助模型解法

本文针对成套产品一维合理下料线性规划模型,给出了一种辅助模型求解方法。实例计算表明,求解方法有效。     

Sequential linear goal programming: Implementation via MPSX

This paper presents the actual results obtained when a traditional linear programming computer code is used sequentially so as to solve the linear goal programming problem. The approach, denoted as Sequential Linear Goal Programming (SLGP), was implemented by incorporating the IBM linear programming code known as MPSX. The results obtained, the advantages and drawbacks, as well as a comparison with an alternate linear goal programming code, are also described.     

On a decision procedure for quantified linear programs

Quantified linear programming is the problem of checking whether a polyhedron specified by a linear system of inequalities is non-empty, with respect to a specified quantifier string. Quantified linear programming subsumes traditional linear programming, since in traditional linear programming, all the program variables are existentially quantified (implicitly), whereas, in quantified linear programming, a program variable may be existentially quantified or universally quantified over a continuous range. In this paper, the term linear programming is used to describe the problem of checking whether a system of linear inequalities has a feasible solution. On account of the alternation of quantifiers in the specification of a quantified linear program (QLP), this problem is non-trivial. QLPs represent a class of declarative constraint logic programs (CLPs) that are extremely rich in their expressive power. The complexity of quantified linear programming for arbitrary constraint matrices is unknown. In this paper, we show that polynomial time decision procedures exist for the case in which the constraint matrix satisfies certain structural properties. We also provide a taxonomy of quantified linear programs, based on the structure of the quantifier string and discuss the computational complexities of the constituent classes. This research has been supported in part by the Air Force Office of Scientific Research under contract FA9550-06-1-0050.     

系数为对称梯形模糊数的模糊线性规划

针对模糊系数的线性规划, 提出了一种系数为对称梯形模糊数的线性规划的方法, 同时得出一些定理、命题以及相应的算法, 并通过实例验证了该方法的有效性. 该方法与常规方法的不同之处在于无须将模糊线性规划转化为经典线性规划就能得到满意的模糊优化解, 因此提出的方法所取得的规划结果更加满足决策者的需要.     

一类One to One营销优化模型及其解决方案

针对OnetoOne营销问题进行简单的案例分析,得出了在一般情况下的优化模型。通过把OnetoOne营销优化问题转换成线性规划问题,应用改进的单纯形法、基于Bartels-GolubLU分解的单纯形法和原始-对偶内点法等三种典型的线性规划算法,在MATLAB环境下进行仿真和分析。     

Training twin support vector regression via linear programming

This paper improves the recently proposed twin support vector regression (TSVR) by formulating it as a pair of linear programming problems instead of quadratic programming problems. The use of 1-norm distance in the linear programming TSVR as opposed to the square of the 2-norm in the quadratic programming TSVR leads to the better generalization performance and less computational time. The effectiveness of the enhanced method is demonstrated by experimental results on artificial and benchmark datasets.     

Investment planning for the development of a national resource —linear programming based approaches

This paper will review and generalize the work of Gearing, Swart and Var dealing with the development of a mathematical model to aid the government of Turkey in determining the “best” allocation of the capital budget for tourism among a large group of competing proposals. One of the more unique aspects of this work was the development of a measure of benefit for particular allocation plans which allowed for subjective information to be an integral part of the investment planning model.The computational procedures developed heretofore to derive investment strategies from the model have been based on dynamic programming, integer programming or combined dynamic programming-integer programming approaches. This paper will show how various methods based on linear programming yield satisfactory answers to many questions regarding development policies. The primary advantage of these linear programming methods is that they can be implemented with standard linear programming computer packages which are generally available, and hence eliminate the high cost of developing special purpose computer codes.     

The multi-weighted Steiner tree problem: A reformulation by intersection

We propose a new formulation for the multi-weighted Steiner tree (MWST) problem. This formulation is based on the fact that a previously proposed formulation for the problem is non-symmetric in the sense that the corresponding linear programming relaxation bounds depend on the node selected as a root of the tree. The new formulation (the reformulation by intersection) is obtained by intersecting the feasible sets of the models corresponding to each possible root selection for the underlying directed problem. Theoretical results will show that the linear programming relaxation of the new formulation dominates the linear programming relaxation of each of the rooted formulations and is comparable with the linear programming bounds of the best formulation known for the problem. A Lagrangean relaxation scheme derived from the new formulation is also proposed and tested, with quite favourable results, on instances with up to 500 nodes and 5000 edges.     

灰色二层多目标线性规划问题及其解法

针对二层多目标线性规划问题,结合灰色系统的特性,提出了一般灰色二层多目标线性规划问题,并给出了模型的相关定义和定理.针对漂移型灰色二层多目标线性规划问题,提出一种具有全局收敛性质的求解算法.首先通过线性加权模理想点法把多目标转化为单目标;然后当可行域为非空紧集时,利用库恩塔克条件把双层转化为单层,再利用粒子群算法搜索单目标单层线性规划即可得到原问题的解;最后通过算例表明了该算法的有效性.     

Discretization method for semi-definite programming

Semi-definite programs are convex optimization problems arising in a wide variety of applications and the extension of linear programming. Most methods for linear programming have been generalized to semi-definite programs. This paper discusses the discretization method in semi-definite programming. The convergence and the convergent rate of error between the optimal value of the semi-definite programming problems and the optimal value of the discretized problems are obtained. An approximately optimal division is given under certain assumptions. With the significance of the convergence property, the duality result in semi-definite programs is proved in a simple way which is different from the other common proofs.     

Linear programming with fuzzy coefficients in constraints

This paper presents a new method for solving linear programming problems with fuzzy coefficients in constraints. It is shown that such problems can be reduced to a linear semi-infinite programming problem. The relations between optimal solutions and extreme points of the linear semi-infinite program are established. A cutting plane algorithm is introduced with a convergence proof, and a numerical example is included to illustrate the solution procedure.