python实现线性规划

python工具包scipy linprog

函数格式

scipy.optimize.

linprog

(c, A_ub=None, b_ub=None, A_eq=None, b_eq=None, bounds=None, method='simplex', callback=None, options=None)官方文档 https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.linprog.html实例minmize: -7x1+7x2-2x3-x4-6x5s.t.: 3x1-x2+x3-2x4=-3 2x1+x2+x4+x5=4 -x1+3x2-3x4+x6=12 xi>=0程序代码：

import numpy as np
import matplotlib.pyplot as mpl
from scipy import optimize
c=np.array([-7,7,-2,-1,-6,0])
a=np.array([[3,-1,1,-2,0,0],[2,1,0,1,1,0],[-1,3,0,-3,0,1]])
b=np.array([-3,4,12])

res=optimize.linprog(c,A_eq=a,b_eq=b,bounds=((0,None),(0,None),(0,None),(0,None),(0,None),(0,None)))
print (res.x)
print (res.fun)

glpk求解



答案一致。