# Mechanism Design With Predictions for Obnoxious Facility Location

arXiv: https://arxiv.org/abs/2212.09521 · HTML: https://mlsanity.com/paper/2212.09521/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 34 references that are in the map.
- First posted on arXiv 19 Dec 2022.

## Builds on (most cited first, 9 of 9)

- [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)
- [Improved Price of Anarchy via Predictions](https://mlsanity.com/paper/2205.04252/) (2022)
- [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 Scheduling with Predictions](https://mlsanity.com/paper/2209.04058/) (2022)
- [Strategyproof Mechanisms for One-Dimensional Hybrid and Obnoxious Facility Location](https://mlsanity.com/paper/1412.3414/) (2014)
- [Strategyproof Facility Location for Three Agents on a Circle](https://mlsanity.com/paper/1902.08070/) (2019)
- [The Obnoxious Facility Location Game with Dichotomous Preferences](https://mlsanity.com/paper/2109.05396/) (2021)

## Built on by (most cited first, 4 of 4)

- [MAC Advice for Facility Location Mechanism Design](https://mlsanity.com/paper/2403.12181/) (2024)
- [On multiagent online problems with predictions](https://mlsanity.com/paper/2507.12486/) (2025)
- [Mechanism Design for Facility Location using Predictions](https://mlsanity.com/paper/2508.03818/) (2025)
- [Impartial Selection with Predictions](https://mlsanity.com/paper/2510.19002/) (2025)

## Abstract (arXiv)

We study mechanism design with predictions for the obnoxious facility location problem. We present deterministic strategyproof mechanisms that display tradeoffs between robustness and consistency on segments, squares, circles and trees. All these mechanisms are actually group strategyproof, with the exception of the case of squares, where manipulations from coalitions of two agents exist. We prove that these tradeoffs are optimal in the 1-dimensional case.