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线性规划问题是求一类线性目标函数在线性约束条件下的最大值或最小值的问题,它的基本思想是借助平面图形,利用线性目标函数的几何意义,有效地解决二元线性目标函数的最值问题.借助此思想,当已知二元变量满足的约束条件并等价转化为图形,而且目标函数具有明确的几何意义时,我们便可较快捷地研究此类二元函数的最值.具体有以下几类几何意义.一、目标函数的几何意义可以转化为截距例1(2013年江苏高考题)抛物线y=
The problem of linear programming is to find the maximum or minimum of a linear objective function under the linear constraints. The basic idea of the linear programming is to solve the problem of binary linear objective function by means of plane graph and the geometric meaning of linear objective function With this idea, when we know the constraints that the binary variables satisfy and transform them into graphs equivalently, and the objective function has a clear geometric meaning, we can quickly and easily study the maximum value of such a binary function There are several specific geometric meanings. First, the geometric meanings of the objective function can be converted into intercept Example 1 (Jiangsu 2013 college entrance examination) Parabolic y =