python求解（线性和二次）规划问题_混合整数二次规划求解器python

理论

二次规划标准形式：

python对应解决问题的代码：

from cvxopt import matrix
import cvxopt.solvers as sol
result = sol.qp(P, Q, G, h, A, b)
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两个例子

1、线性
问题：（此问题中没有p,q）

代码：

 from cvxopt import matrix, solvers
 A = matrix([ [-1.0, -1.0, 0.0, 1.0], [1.0, -1.0, -1.0, -2.0] ])
 b = matrix([ 1.0, -2.0, 0.0, 4.0 ])
 c = matrix([ 2.0, 1.0 ])
 sol=solvers.lp(c,A,b)
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2、二次

 from cvxopt import matrix, solvers
 Q = 2*matrix([ [2, .5], [.5, 1] ])
 p = matrix([1.0, 1.0])
 G = matrix([[-1.0,0.0],[0.0,-1.0]])
 h = matrix([0.0,0.0])
 A = matrix([1.0, 1.0], (1,2))#原型为cvxopt.matrix(array,dims)，等价于A = matrix([[1.0],[1.0]]）
b = matrix(1.0)
sol=solvers.qp(Q, p, G, h, A, b)
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参考：
https://cvxopt.org/examples/tutorial/qp.html