# Mechanism Design for Facility Location using Predictions

arXiv: https://arxiv.org/abs/2508.03818 · HTML: https://mlsanity.com/paper/2508.03818/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 29 references that are in the map.
- First posted on arXiv 5 Aug 2025.

## Builds on (most cited first, 13 of 13)

- [Algorithms with Predictions](https://mlsanity.com/paper/2006.09123/) (2020)
- [Learning-Augmented Mechanism Design: Leveraging Predictions for Facility Location](https://mlsanity.com/paper/2204.01120/) (2022)
- [Mechanism Design for Facility Location Problems: A Survey](https://mlsanity.com/paper/2106.03457/) (2021)
- [Online Facility Location with Predictions](https://mlsanity.com/paper/2110.08840/) (2021)
- [Facility Location Problem with Capacity Constraints: Algorithmic and Mechanism Design Perspectives](https://mlsanity.com/paper/1911.09813/) (2019)
- [Mechanism Design with Predictions](https://mlsanity.com/paper/2205.11313/) (2022)
- [Strategyproof and Proportionally Fair Facility Location](https://mlsanity.com/paper/2111.01566/) (2021)
- [Optimality of the coordinate-wise median mechanism for strategyproof facility location in two dimensions](https://mlsanity.com/paper/2007.00903/) (2020)
- [Strategy Proof Mechanisms for Facility Location at Limited Locations](https://mlsanity.com/paper/2009.07982/) (2020)
- [Mechanism Design With Predictions for Obnoxious Facility Location](https://mlsanity.com/paper/2212.09521/) (2022)
- [Mechanism Design for Facility Location Games with Candidate Locations](https://mlsanity.com/paper/2010.09640/) (2020)
- [A Survey on Approximation Mechanism Design without Money for Facility Games](https://mlsanity.com/paper/1503.07426/) (2015)
- [Optimizing Multiple Simultaneous Objectives for Voting and Facility Location](https://mlsanity.com/paper/2212.03467/) (2022)

## Abstract (arXiv)

We study mechanisms for the facility location problem augmented with predictions of the optimal facility location. We demonstrate that an egalitarian viewpoint which considers both the maximum distance of any agent from the facility and the minimum utility of any agent provides important new insights compared to a viewpoint that just considers the maximum distance. As in previous studies, we consider performance in terms of consistency (worst case when predictions are accurate) and robustness (worst case irrespective of the accuracy of predictions). By considering how mechanisms with predictions can perform poorly, we design new mechanisms that are more robust. Indeed, by adjusting parameters, we demonstrate how to trade robustness for consistency. We go beyond the single facility problem by designing novel strategy proof mechanisms for locating two facilities with bounded consistency and robustness that use two predictions for where to locate the two facilities.