线性规划问题

线性规划问题的F解决方案

The Fuzzy Scheme to the Linear Programming problem

如何利用EXCEL求解线性规划问题及其灵敏度分析

Solution of Linear Programming Problem and Sensitivity Analysis by Excel

关于Fuzzy约束条件下多目标线性规划问题方法的改进

Improvement for the solution of multi-objective linear programming under the constraint condition of Fuzzy

利用多群体DNA遗传算法求解线性规划问题

Using DNA Genetic Algorithm With Multi-Population to Solve Linear Programming

用演化Agent方法处理整数线性规划问题

An evolutionary agent approach to integer linear programming

基于Agent的整数线性规划问题的求解算法

An Agent-based Algorithm for Integer Linear Programming

关于推广的线性规划问题的BP网络求解

On the solution of extended linear programming by using BP neural networks

描述了一种演化agent模型，并用这种模型来处理整数线性规划问题。

This paper presents an evolutionary agent model and used it to deal with the problem of integer linear programming .

利用Excel求解线性规划问题

Use of Excel to Solve the Problems of Linear Programming

对此，本文第四章总结了区间线性规划问题基B稳定的概念，探讨了区间线性规划问题的三种类型。

This fourth chapter summarizes B stability of the interval linear programming problem and studies the three types of interval linear programming problems .

在求解变量无非负约束且含有等式约束的完全型区间线性规划问题时基B稳定起着关键作用。

B stability plays a key role in solving fully interval linear programming problem that has equality constraints and have no conditions for variables .

自反Banach空间中锥线性规划问题的几何性质

Geometry Property of Conic Linear Optimization in Reflexive Banach Spaces

利用Excel工具箱中的规划求解虽然可以解一些线性规划问题，但是直接求解在Excel工作表上表达的步骤较多，求解过程繁琐。

With numerous operational procedures , linear programming solver in Excel toolbox is a complicated solution .

从计算复杂度来讲，整数线性规划问题是已知的NP难的。

Considering computational complexity , integer linear programming is one of the known NP-hard problems .

针对上层有约束条件、下层有N个独立的决策单元的二层线性规划问题，提出了一种模糊数学解法。

A fuzzy mathematical approach is proposed for bi level programming problems in which the upper level has constraints and the lower level consists of N independent programming units .

G.Bland提出了求解退化线性规划问题的Bland法则，这些方法都能避免循环发生。

It can avoid circulation to solve the degenerate linear programming based on the simple method .

直接解规范型线性规划问题的Karmarkar算法

Karmarkar algorithm for solving directly the normal LP

GMM法计算量少、按参考文献[1]的数学模型在计算机上实现速度快，利于求解大规模多目标线性规划问题。

It has less amount of calculation and a high speed of computation , which is help-ful to solve the large scale multi-objective linear programme problems .

二十世纪八十年代，美国著名物理学家Hopfield和Tank提出用人工神经网络方法求解线性规划问题，从此以后，这一领域的研究和应用得到了越来越多的关注。

In 1980s , Hopfield and Tank proposed a novel artificial neural network for solving linear programming problems . From then on , more and more attentions have been paid in research and application of such area .

针对该模型的特殊结构，提出了一种将原问题转化为等价的多个线性规划问题，然后使用Excel标准线性规划程序求解的策略。

In view of the special structure of the model , a solution strategy by decomposing the original model into several linear programming models , which could be solved through standard linear programming software from EXCEL , was proposed .

假若商业银行采取现金中性（cashneutrality）的资产交易策略，风险计量模型可转换为线性规划问题，从而可以构建基于利率风险最小化模型的随机免疫策略。

That if commercial banks adopt a cash-neutrality trade strategy , risk econometrics modeling can be transformed to linearity program problem . Thus , this paper builds up stochastic immunization strategy on basis of minimizing interest-rate risks model , i. e.

此外，收费员排班是一个整数规划问题，而整数规划属于典型的NP难解问题，本文采用了基于遗传规划的整数线性规划问题求解方法来解决收费员排班问题。

In addition , the job scheduling of toll collector is an integer programming problem , and integer programming is a kind of typical NP hard problem which is solved usually by genetic algorithm ( GA ) .

本文给出求解线性规划问题的一种改进的Karmarkar算法IKA。

In this paper an improved version of Karmarkar algorithm ( IKA ) for linear programming and its convergence analysis are given .

首先，利用非线性变换将线性规划问题转化为一无约束非线性方程组，然后用ABS方法求解，据此再求得LP问题的最优解。

First a nonlinear transform is used to change a LP problem into an unrestriced nonlinear algebraic equations ; then the equations is solved by a ABS method . Last the optimum solution of the LP problem is obtained .

同时阐述了如何将对偶线性规划问题转化为LCP问题的方法，由此获得计算对偶线性规划问题的区间迭代算法。

Besides , a method is introduced to transfer the dual linear programming problem into LCP , thus , the interval iterative algorithm for the dual linear programming problem is obtained .

单纯形法和Karmarkar算法及其变形算法是解线性规划问题的三个不同算法，本文从实例出发，对三种算法进行了比较和分析。

There are three different methods to solve linear programming problems : simplical method , Karmarkar and the transmutative algorithm . The paper makes comparison and analysis through examples .

求解线性规划问题在目前实际应用中都是采用的原始单纯形法。本文论证了单纯形方法中用Bland方法要比原始单纯形方法为优。

At the present time the original simplex method is still used predominantly in solving practical linear programming problems . This paper expounds and proves that the simplex method adopting Blands theory is better than the original simplex method .

通过引入松驰变量、剩余变量和人工变量，构造辅助目标函数Z1，以及应用换基运算，使线性规划问题得以简化。

First , by introducing flabby variable , remnant variable and artificial variable to form auxiliary object function Z1 , and in addition applying operation of exchanging radix , the question of linearity planning is simplified ;

通过把这类问题转化为一般的多目标线性规划问题，并利用交互规划的修正Z-W法进行求解，从而有效地解决这类问题。

This model can be converted into a common multi objective linear programming , which can be efficiently solved by the corrected Z W method of interactive programming algorithm .

为方便计算，将求取最优解的线性规划问题转化为一个关于有界变量的BVLP（有界变量线性规划）问题。

The linear programming problem for optimal solution can also be converted to a BVLP ( bounded variables linear programming ) problem for the simplicity of computation .