例子：对下面方程进行求解，

1 先标准化

python求解线性规划 python求解线性规划的函数_最小值

#导入包
from scipy import optimize
import numpy as np

#确定c,A,b,Aeq,beq
c = np.array([2,3,-5])
A = np.array([[-2,5,-1],[1,3,1]])
b = np.array([-10,12)]
Aeq = np.array([[1,1,1]])
beq = np.array([7])

#求解
res = optimize.linprog(-c,A,b,Aeq,beq)
print(res)
'''
     fun: -14.571428571428571   目标函数最小值
 message: 'Optimization terminated successfully.'     优化是否成功
     nit: 2
   slack: array([3.85714286, 0.        ])
  status: 0
 success: True
       x: array([6.42857143, 0.57142857, 0.        ])   x的最优解

'''