The purpose of this repo is to provide easy-to-play-with pieces of code, to illustrate various fair division notions and protocols. More specifically, we follow the following chapter:

Bouveret, Sylvain, Chevaleyre, Yann et Maudet, Nicolas (2016). Fair Allocation of Indivisible Goods. In Brandt, Felix, Conitzer, Vincent, Endriss, Ulle, Lang, Jérôme et Procaccia, Ariel D., éditeurs, Handbook of Computational Social Choice, Chapitre 12.Cambridge University Press.

The code is divided in four main modules:

• problem.py allows to define various problems
• fairnessmeasures.py defines different functions to compute fairness measures
• mipsolving.py implements MIP formulations for fair optimisation problems
• protocols.py implements several protocols discussed in the chapter (adjusted winner, picking sequences, Liption et al., etc.)

It is accompanied with a Jupyter Notebook illustrating the different notions.

Requires to have installed:

• Pulp