1. sciPy优化算法包
   sciPy中的optimize中的函数linprog使用simplex方法来求解线性规划问题，但是这个算法包不能求解整数规划问题。
   官方例子：

from scipy import optimize as op
import numpy as np
c=np.array([2,3,-5])
A_ub=np.array([[-2,5,-1],[1,3,1]])
B_ub=np.array([-10,12])
A_eq=np.array([[1,1,1]])
B_eq=np.array([7])
x1=(0,7)
x2=(0,7)
x3=(0,7)
res=op.linprog(-c,A_ub,B_ub,A_eq,B_eq,bounds=(x1,x2,x3))
print(res)

输出结果为：

     fun: -14.571428571428571
 message: 'Optimization terminated successfully.'
     nit: 2
   slack: array([3.85714286, 0.57142857, 6.42857143, 7.        , 0.        ])
  status: 0
 success: True
       x: array([6.42857143, 0.57142857, 0.        ])

2. pulp算法包
   参考https://pythonhosted.org/PuLP/index.html。PuLP is an LP modeler written in python. PuLP can generate MPS or LP files and call GLPK[1], COIN CLP/CBC[2], CPLEX[3], and GUROBI[4] to solve linear problems.
3. 调用