What Quadratic Programming Package?

[lucag]

Hello everyone,

what quadratic programming package will you be using for HW#7?

I looked it up a bit online and found a few, but I am curious to hear from the class.
My programming language of choice is Matlab/Octave (I know Python and C++ too but I am more comfortable with Matlab/Octave), for which I found http://www.mat.univie.ac.at/~neum/software/minq/ ... but I am a bit reticent to use a package I've never tried before.

Thanks!

[kkkkk]

I am using python and it seems that cvxopt is the commonly used free library.

[IamMrBB]

Originally Posted by kkkkk

I am using python and it seems that cvxopt is the commonly used free library.

that's the one i used as well

[marcello]

Is there one such lib that can work on Windows?
Thanks

[dudefromdayton]

In this thread, I describe one alternative for Mathematica users, and the ups and downs of that approach.

[lucag]

Thanks for the input ... I found the CVX library for Matlab and I will (try to) use that.
@Marcello I don't think any of those libraries are system specific, i.e., they can be used on a Mac as well as on Windows, or Linux, or BSD, or ...

[mathprof]

I also used Python with cvxopt. It seemed to work fine.

[marcello]

Found Win64 installer here: http://www.lfd.uci.edu/~gohlke/pythonlibs/
(great Python resource)

Whitout the installer, it's a nightmare :S

[jbaker]

Anybody tried this in R? The solve.QP function in the quadprog library sounds very promising, but it complains about the first matrix not being positive definite (unless I set factorized=T, which doesn't sound right -- Dmat here is the same as what's called Q on the lecture slide, correct?).



solve.QP package:quadprog R Documentation

Solve a Quadratic Programming Problem

Description:

This routine implements the dual method of Goldfarb and Idnani
(1982, 1983) for solving quadratic programming problems of the
form min(-d^T b + 1/2 b^T D b) with the constraints A^T b >= b_0.

Usage:

solve.QP(Dmat, dvec, Amat, bvec, meq=0, factorized=FALSE)

Arguments:

Dmat: matrix appearing in the quadratic function to be minimized.

dvec: vector appearing in the quadratic function to be minimized.

Amat: matrix defining the constraints under which we want to
minimize the quadratic function.

bvec: vector holding the values of b_0 (defaults to zero).

meq: the first ‘meq’ constraints are treated as equality
constraints, all further as inequality constraints (defaults
to 0).

factorized: logical flag: if ‘TRUE’, then we are passing R^(-1) (where
D = R^T R) instead of the matrix D in the argument ‘Dmat’.

[forecaster]

I had the same problem with solve.QP.

Try ipop (kernlab package) and it will work.