python，matlab,C++ 凸优化库——anaconda spyder->cvxpy,matlab->cvx,C++->qpOASES

python:

使用spyder安装所需库，包时需要在控制台输入命令

!pip install xxxx

但是有可能源不太好，导致安装失败

因此最好去官网下载，然后将下载包放置到工作空间，使用!pip install xxx文件名

下面以cvxpy凸优化包为例

下载对应版本包

cvxpy下载处

将包移至工作空间，使用在控制台输入命令!pip install cvxpy-1.0.10-cp36-cp36m-win_amd64.whl

ok

简单示例：

import cvxpy as cvx 
#定义优化变量 
x = cvx.Variable() 
y = cvx.Variable() 
# 定义约束条件
constraints = [x + y == 1, 
               x - y >= 1] 
# 定义优化问题 
obj = cvx.Minimize((x - y)**2) 
# 定义优化问题 
prob = cvx.Problem(obj, constraints) #求解问题
prob.solve() #返回最优值
print("status:", prob.status)#求解状态 
print("optimal value", prob.value) #目标函数优化值 
print("optimal var", x.value, y.value) #优化变量的值，相应变量加.value

matlab:

matlab凸优化工具箱下载处

cvx使用说明pdf链接

m = 20; n = 10; p = 4;
A = randn(m,n); b = randn(m,1);
C = randn(p,n); d = randn(p,1); e = rand;
cvx_begin
    variable x(n)
    minimize( norm( A * x - b, 2 ) )
    subject to
        C * x == d
        norm( x, Inf ) <= e
cvx_end

C++ ：

qpOASES采用可行集策略，规模越大耗时越长

qpOASES下载处

示例、

#include "include\qpOASES.hpp"

int main()
{
    USING_NAMESPACE_QPOASES
    /* Setup data of first QP. */
    real_t H[2 * 2] = { 1.0, 0.0, 0.0, 0.5 };
    real_t A[1 * 2] = { 1.0, 1.0 };
    real_t g[2] = { 1.5, 1.0 };
    real_t lb[2] = { 0.5, -2.0 };
    real_t ub[2] = { 5.0, 2.0 };
    real_t lbA[1] = { -1.0 };
    real_t ubA[1] = { 2.0 };
    /* Setup data of second QP. */
    real_t g_new[2] = { 1.0, 1.5 };
    real_t lb_new[2] = { 0.0, -1.0 };
    real_t ub_new[2] = { 5.0, -0.5 };
    real_t lbA_new[1] = { -2.0 };
    real_t ubA_new[1] = { 1.0 };
    /* Setting up QProblem object. */
    QProblem example(2, 1);
    /* Solve first QP. */
    int_t nWSR = 10;
    example.init(H, g, A, lb, ub, lbA, ubA, nWSR);
    /* Solve second QP. */
    nWSR = 10;
    example.hotstart(g_new, lb_new, ub_new, lbA_new, ubA_new, nWSR);
    /* Get and print solution of second QP. */
    real_t xOpt[2];
    example.getPrimalSolution(xOpt);
    printf("\n xOpt = [ %e, %e ]; objVal = %e\n\n",
        xOpt[0], xOpt[1], example.getObjVal());
    return 0;
}

后续增加 ：

由于python又方便可用的cvxpy包，是否可以用c/c++调用python的包cvxpy

https://docs.python.org/2/extending/embedding.html