Optimal Efficiency-Envy Trade-Off via Optimal Transport

Steven Yin, Christian Kroer

Keywords: Resource Allocation, Fair Division, Optimal Transport

TL;DR: We use tools from Optimal Transport to achieve optimal trade-off between efficiency and envy in resource allocation problems.

Abstract: We consider the problem of allocating a distribution of items to $n$ recipients where each recipient has to be allocated a fixed, pre-specified 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.

Community Implementations: [ 1 code implementation](https://www.catalyzex.com/paper/arxiv:2209.15416/code)