Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism
Haris Aziz, Alexander Lam, Mashbat Suzuki, Toby Walsh
Abstract
Proportionality is an attractive fairness concept that has been applied to a range of problems including the facility location problem, a classic problem in social choice. In our work, we propose a concept called Strong Proportionality, which ensures that when there are two groups of agents at different locations, both groups incur the same total cost. We show that although Strong Proportionality is a well-motivated and basic axiom, there is no deterministic strategyproof mechanism satisfying the property. We then identify a randomized mechanism called Random Rank (which uniformly selects a number between to and locates the facility at the 'th highest agent location) which satisfies Strong Proportionality in expectation. Our main theorem characterizes Random Rank as the unique mechanism that achieves universal truthfulness, universal anonymity, and Strong Proportionality in expectation among all randomized mechanisms. Finally, we show via the AverageOrRandomRank mechanism that even stronger ex-post fairness guarantees can be achieved by weakening universal truthfulness to strategyproofness in expectation.
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Cited by top-tier papers2
- Altruism in Facility Location ProblemsHouyu Zhou, Hau Chan, Minming LiAAAI 2024 · 5 citations
- Learning-Augmented Facility Location Mechanisms for Envy RatioHaris Aziz, Yuhang Guo, Alexander Lam, Houyu ZhouNeurIPS 2025 · 1 citation
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