使用CVXOPT进行Python二次编程

Question

I am looking for a definitive guide on formulating a CVXOPT quadratic programming problem with quadratic constraints. There are good documents provided here:

The problem statement I am dealing with is identical to the problem here :

What is the matrix G supposed to look like? I've formulated as a system of linear equations, but looking at examples this does not appear to be correct?

The best resource I've found is https://courses.csail.mit.edu/6.867/wiki/images/a/a7/Qp-cvxopt.pdf , but the links at the end are dead for more reading.

I have an ipython notebook trying to use this programming method but it continually fails: https://gist.github.com/jaredvacanti/62010beda0ccfc20d2eac3c900858e50

Edit: I have edited the data source file in the notebook to provide access to the real data used in this optimization problem.

Answer 1

The notebook you have posted seems to have it all figured out. The problem I had is that the source file for data is not available.

Now to your question:

What is the matrix G supposed to look like? I've formulated as a system of linear equations, but looking at examples this does not appear to be correct?

Rewrite your "linear equations" into matrix form, ie

2x + 2y = 4
x  - y  = 1

is equivalent to

matrix([[2,2],[1,-1]]) * matrix([[x],[y]])  = matrix([[4],[1]])

where matrix is from cvxopt .