Jupyter notebooks with implementations and solutions to optimization problems found in Model Building in Mathematical Programming by H. Paul Williams(*).
This is not the intended final version of these codes, as I plan to improve their documentation, with more comments like variables description and explanation about model constraints.
This repository is the result of an exercise where I only wanted to practice implementing and solving mathematical optimization problems using the solver Gurobi. Being an exercise, the implementation can be completely original or, when I had difficulties, very similar to the one suggested by Gurobi Team. Their implementation can be found in https://www.gurobi.com/resource/functional-code-examples/
Unlike in their jupyter notebooks, I did not add a problem description.
The package mainly required is gurobipy, that requires a license. Other popular (and free) python packages are sometimes used, too (like pandas, itertools, etc).
(*) Williams, H. Paul. Model building in mathematical programming. John Wiley & Sons, 5th Edition, 2013.