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Proportional Fairness in Obnoxious Facility Location

  • Alexander Lam
  • , Haris Aziz
  • , Bo Li
  • , Fahimeh Ramezani
  • , Toby Walsh

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

We consider the obnoxious facility location problem (in which agents prefer the facility location to be far from them) and propose a hierarchy of distance-based proportional fairness concepts for the problem. These fairness axioms ensure that groups of agents at the same location are guaranteed to be a distance from the facility proportional to their group size. We consider deterministic and randomized mechanisms, and compute tight bounds on the price of proportional fairness. In the deterministic setting, we show that our proportional fairness axioms are incompatible with strategyproofness, and prove asymptotically tight epsilon-price of anarchy and stability bounds for proportionally fair welfare-optimal mechanisms. In the randomized setting, we identify proportionally fair and strategyproof mechanisms that give an expected welfare within a constant factor of the optimal welfare. Finally, we prove existence results for two extensions to our model. © 2024 International Foundation for Autonomous Agents and Multiagent Systems.
Original languageEnglish
Title of host publicationAAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems
Place of PublicationRichland, SC
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1075-1083
ISBN (Print)979-8-4007-0486-4
Publication statusPublished - May 2024
Event23th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024) - Auckland, New Zealand
Duration: 6 May 202410 May 2024
https://www.aamas2024-conference.auckland.ac.nz/
https://dl.acm.org/doi/proceedings/10.5555/3635637

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403

Conference

Conference23th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024)
Abbreviated titleAAMAS '24
PlaceNew Zealand
CityAuckland
Period6/05/2410/05/24
Internet address

Funding

Bo Li is funded by NSFC under Grant No. 62102333 and HKSAR RGC under Grant No. PolyU 15224823.

Research Keywords

  • Approximate Equilibria
  • Facility location
  • Fairness
  • Social choice

RGC Funding Information

  • RGC-funded

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