# Finding Fair and Efficient Allocations When Valuations Don't Add Up

arXiv: https://arxiv.org/abs/2003.07060 · HTML: https://mlsanity.com/paper/2003.07060/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Mar 2020.

## Built on by (most cited first, 5 of 5)

- [Yankee Swap: a Fast and Simple Fair Allocation Mechanism for Matroid Rank Valuations](https://mlsanity.com/paper/2206.08495/) (2022)
- [Multilevel Fair Allocation with Matroid-Rank Preferences](https://mlsanity.com/paper/2512.24105/) (2025)
- [Dividing Good and Better Items Among Agents with Bivalued Submodular Valuations](https://mlsanity.com/paper/2302.03087/) (2023)
- [Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Division](https://mlsanity.com/paper/2507.14957/) (2025)
- [Fair Division with Strictly Increasing Valuations: A Tight Threshold for Two-Agent EF1 and PO](https://mlsanity.com/paper/2607.23367/) (2026)

## Abstract (arXiv)

In this paper, we present new results on the fair and efficient allocation of indivisible goods to agents whose preferences correspond to em matroid rank functions. This is a versatile valuation class with several desirable properties (such as monotonicity and submodularity), which naturally lends itself to a number of real-world domains. We use these properties to our advantage; first, we show that when agent valuations are matroid rank functions, a socially optimal (i.e. utilitarian social welfare-maximizing) allocation that achieves envy-freeness up to one item (EF1) exists and is computationally tractable. We also prove that the Nash welfare-maximizing and the leximin allocations both exhibit this fairness/efficiency combination, by showing that they can be achieved by minimizing any symmetric strictly convex function over utilitarian optimal outcomes. To the best of our knowledge, this is the first valuation function class not subsumed by additive valuations for which it has been established that an allocation maximizing Nash welfare is EF1. Moreover, for a subclass of these valuation functions based on maximum (unweighted) bipartite matching, we show that a leximin allocation can be computed in polynomial time. Additionally, we explore possible extensions of our results to fairness criteria other than EF1 as well as to generalizations of the above valuation classes.