TITLE: How to convert quadratic programming problem to matrix form
QUESTION [6 upvotes]: I am new to this topic and am looking at an example I can't figure out.  Can someone please help explain how this example creates the matrices used in the solver?  Thanks!
This is the PROBLEM

Minimize $2x_1^2 + x_2^2 + x_1x_2 + x_1 + x_2,\quad$subject to:
$x_1 \geq 0$
$x_2 \geq 0$
$x_1 + x_2 = 1$

ANSWER:
Matrix Form for solver:
Q = [4.0, 1.0]
[1.0, 2.0]
p = [1.0]
[1.0]
G = [-1.0, 0.0]
[0.0, -1.0]
h = [0.0]
[0.0]
A = [1.0, 1.0]
b = [1.0]
result = solve.qp(Q, p, G, h, A, b)

REPLY [3 votes]: It looks like you're trying to solve a quadratic program of the form:
$$
\begin{aligned}
& \underset{x}{\text{minimize}}
& & \frac{1}{2} x^T Q x + p^T x \\
& \text{subject to}
& & Gx \preceq h \\
&&& Ax = b
\end{aligned}
$$
Expand the objective function where $x = \left [x_1 \quad x_2 \right ]^T$ and you will see that
$$\frac{1}{2}
\begin{bmatrix} x_1 & x_2 \end{bmatrix}\begin{bmatrix} 4 & 1 \\ 1 & 2 \end{bmatrix} 
\begin{bmatrix} x_1 \\ x_2 \end{bmatrix} + \begin{bmatrix} 1 & 1 \end{bmatrix}\begin{bmatrix} x_1 \\ x_2 \end{bmatrix} = (2x_1^2 + x_2^2 + x_1x_2) + (x_1 + x_2)
$$.
Similarly, expand $Gx \preceq h$ and $Ax = b$ and you'll see that they are equivalent to $x_1,x_2 \ge 0$ and $x_1+x_2 = 1$ respectively.