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Facility location with double-peaked preferences

Published: 01 November 2017 Publication History

Abstract

We study the problem of locating a single facility on a real line based on the reports of self-interested agents, when agents have double-peaked preferences, with the peaks being on opposite sides of their locations. We observe that double-peaked preferences capture real-life scenarios and thus complement the well-studied notion of single-peaked preferences. As a motivating example, assume that the government plans to build a primary school along a street; an agent with single-peaked preferences would prefer having the school built exactly next to her house. However, while that would make it very easy for her children to go to school, it would also introduce several problems, such as noise or parking congestion in the morning. A 5-min walking distance would be sufficiently far for such problems to no longer be much of a factor and at the same time sufficiently close for the school to be easily accessible by the children on foot. There are two positions (symmetrically) in each direction and those would be the agent's two peaks of her double-peaked preference. Motivated by natural scenarios like the one described above, we mainly focus on the case where peaks are equidistant from the agents' locations and discuss how our results extend to more general settings. We show that most of the results for single-peaked preferences do not directly apply to this setting, which makes the problem more challenging. As our main contribution, we present a simple truthful-in-expectation mechanism that achieves an approximation ratio of $$1+b/c$$1+b/c for both the social and the maximum cost, where b is the distance of the agent from the peak and c is the minimum cost of an agent. For the latter case, we provide a 3 / 2 lower bound on the approximation ratio of any truthful-in-expectation mechanism. We also study deterministic mechanisms under some natural conditions, proving lower bounds and approximation guarantees. We prove that among a large class of reasonable strategyproof mechanisms, there is no deterministic mechanism that outperforms our truthful-in-expectation mechanism. In order to obtain this result, we first characterize mechanisms for two agents that satisfy two simple properties; we use the same characterization to prove that no mechanism in this class can be group-strategyproof.

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  • (2024)On the capacitated facility location problem with scarce resourcesProceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence10.5555/3702676.3702684(186-202)Online publication date: 15-Jul-2024
  • (2024)Facility Location Games with Fractional Preferences and Limited ResourcesProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662906(553-561)Online publication date: 6-May-2024
  • (2024)Locating Two Facilities on a Square with a Minimum Distance RequirementFrontiers of Algorithmics10.1007/978-981-97-7752-5_23(317-333)Online publication date: 30-Jul-2024
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Information & Contributors

Information

Published In

cover image Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems  Volume 31, Issue 6
November 2017
401 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 November 2017

Author Tags

  1. Approximate mechanism design without money
  2. Double-peaked preferences
  3. Facility location
  4. Maximum cost
  5. Social cost
  6. Strategyproofness

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  • (2024)On the capacitated facility location problem with scarce resourcesProceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence10.5555/3702676.3702684(186-202)Online publication date: 15-Jul-2024
  • (2024)Facility Location Games with Fractional Preferences and Limited ResourcesProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662906(553-561)Online publication date: 6-May-2024
  • (2024)Locating Two Facilities on a Square with a Minimum Distance RequirementFrontiers of Algorithmics10.1007/978-981-97-7752-5_23(317-333)Online publication date: 30-Jul-2024
  • (2024)Mechanism Design with Predictions for Facility Location Games with Candidate LocationsTheory and Applications of Models of Computation10.1007/978-981-97-2340-9_4(38-49)Online publication date: 13-May-2024
  • (2024)The k-Facility Location Problem via Optimal Transport: A Bayesian Study of the Percentile MechanismsAlgorithmic Game Theory10.1007/978-3-031-71033-9_9(147-164)Online publication date: 3-Sep-2024
  • (2023)Facility Location Games with ThresholdsProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598891(2170-2178)Online publication date: 30-May-2023
  • (2023)Settling the Distortion of Distributed Facility LocationProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598889(2152-2160)Online publication date: 30-May-2023
  • (2023)Constrained heterogeneous facility location games with max-variant costJournal of Combinatorial Optimization10.1007/s10878-023-01017-645:3Online publication date: 30-Mar-2023
  • (2022)Budget feasible mechanisms for facility location games with strategic facilitiesAutonomous Agents and Multi-Agent Systems10.1007/s10458-022-09563-936:2Online publication date: 1-Oct-2022
  • (2022)Facility Reallocation on the LineAlgorithmica10.1007/s00453-022-00993-184:10(2898-2925)Online publication date: 1-Oct-2022
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