Optimal Efficiency-Envy Trade-Off via Optimal Transport
Abstract
We consider the problem of allocating a distribution of items to recipients where each recipient has to be allocated a fixed, prespecified fraction of all items, while ensuring that each recipient does not experience too much envy. We show that this problem can be formulated as a variant of the semi-discrete optimal transport (OT) problem, whose solution structure in this case has a concise representation and a simple geometric interpretation. Unlike existing literature that treats envy-freeness as a hard constraint, our formulation allows us to \emph{optimally} trade off efficiency and envy continuously. Additionally, we study the statistical properties of the space of our OT based allocation policies by showing a polynomial bound on the number of samples needed to approximate the optimal solution from samples. Our approach is suitable for large-scale fair allocation problems such as the blood donation matching problem, and we show numerically that it performs well on a prior realistic data simulator.
Keywords
Cite
@article{arxiv.2209.15416,
title = {Optimal Efficiency-Envy Trade-Off via Optimal Transport},
author = {Steven Yin and Christian Kroer},
journal= {arXiv preprint arXiv:2209.15416},
year = {2022}
}