#Using integer programming and portfolio optimization to pick a March Madness bracket
In this notebook I explore the use of an integer program solver in Python to pick an optimal March Madness bracket.
I use the cvxopt Python interface to the glpk solver, both freely available. I also use pandas and numpy. Installing cvxopt and glpk was simple but not completely straightforward; see the appendix at the end for how I did it.
The file bracket-05.tsv is copied from fivethirtyeight.
Read the notebook here: http://nbviewer.ipython.org/github/sharnett/march-madness-2015/blob/master/madness.ipynb
##Installing cvxopt and glpk
I think this should do the trick.
sudo apt-get install libglpk36
export CVXOPT_BUILD_GLPK=1
export CVXOPT_GLPK_LIB_DIR=/usr/lib/x86_64-linux-gnu/
export CVXOPT_GLPK_INC_DIR=/usr/include/
pip install cvxopt
python
> from cvxopt.glpk import ilp
brew install homebrew/science/glpk
export CVXOPT_BUILD_GLPK=1
export CVXOPT_GLPK_LIB_DIR=/usr/local/Cellar/glpk/4.52/lib
export CVXOPT_GLPK_INC_DIR=/usr/local/Cellar/glpk/4.52/include
pip install cvxopt
python
> from cvxopt.glpk import ilp