线性规划是求目标函数在约束条件下的最值,因此在没有变量取整数的约束条件下,最优解只能在可行域的边界或端点处取得,利用此性质,可衍生出许多与边界或端点有关的“擦边球”问题。现举例如下:△ABC中,三顶点A(2,4),B(-1,2),C(1,0),点P (x,y)在△ABC内部及边界运动,则(1)z=x-y的最大值及最小值是分析:将A(2,4)代入目标函数得,z=2-4=-2 Linear programming is to find the value of the objective function under constraint conditions. Therefore, under the constraint that no variable takes an integer, the optimal solution can only be obtained at the boundary or end point of the feasible region. Using this property, many boundaries can be derived. Or “end-of-line” problem with endpoints. An example is as follows: In ABC, the three vertices A(2,4), B(-1,2), C(1,0), point P(x,y) move inside and inside ABC, then (1) ) The maximum and minimum values ​​of z=xy are analysis: Substituting A(2,4) into the objective function, z=2-4=-2