On Voting and Facility Location
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Abstract (arXiv)
We study mechanisms for candidate selection that seek to minimize the social cost, where voters and candidates are associated with points in some underlying metric space. The social cost of a candidate is the sum of its distances to each voter. Some of our work assumes that these points can be modeled on a real line, but other results of ours are more general. A question closely related to candidate selection is that of minimizing the sum of distances for facility location. The difference is that in our setting there is a fixed set of candidates, whereas the large body of work on facility location seems to consider every point in the metric space to be a possible candidate. This gives rise to three types of mechanisms which differ in the granularity of their input space (voting, ranking and location mechanisms). We study the relationships between these three classes of mechanisms. While it may seem that Black's 1948 median algorithm is optimal for candidate selection on the line, this is not the case. We give matching upper and lower bounds for a variety of settings. In particular, when candidates and voters are on the line, our universally truthful spike mechanism gives a [tight] approximation of two. When assessing candidate selection mechanisms, we seek several desirable properties: (a) efficiency (minimizing the social cost) (b) truthfulness (dominant strategy incentive compatibility) and (c) simplicity (a smaller input space). We quantify the effect that truthfulness and simplicity impose on the efficiency.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2015.
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Citing papers per year: 2021: 2; 2022: 4; 2023: 2; 2024: 1; 2025: 0; 2026: 1.
10 papers.
- 2021Strategyproof and Proportionally Fair Facility Locationcited by 6
- 2022Plurality Veto: A Simple Voting Rule Achieving Optimal Metric Distortioncited by 6
- 2022Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanismcited by 3
- 2022Strategic Facility Location with Clients that Minimize Total Waiting Timecited by 3
- 2023Breaking the Metric Voting Distortion Barriercited by 3
- 2022Optimizing Multiple Simultaneous Objectives for Voting and Facility Locationcited by 2
- 2021Facility Reallocation on the Linecited by 1
- 2023Nash Welfare and Facility Locationcited by 1
- 2026Embeddings for Preferences, Not Semanticscited by 1
- 2024Facility Location Games with Scaling Effectscited by 0
- 2026Embeddings for Preferences, Not Semantics8 May 2026
- 2024Facility Location Games with Scaling Effects29 Feb 2024
- 2023Nash Welfare and Facility Location6 Oct 2023
- 2023Breaking the Metric Voting Distortion Barrier30 Jun 2023
- 2022Optimizing Multiple Simultaneous Objectives for Voting and Facility Location7 Dec 2022
- 2022Strategic Facility Location with Clients that Minimize Total Waiting Time25 Nov 2022
- 2022Plurality Veto: A Simple Voting Rule Achieving Optimal Metric Distortion14 Jun 2022
- 2022Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism30 May 2022
- 2021Strategyproof and Proportionally Fair Facility Location2 Nov 2021
- 2021Facility Reallocation on the Line23 Mar 2021