Fair division with two-sided preferences

We study a fair division setting in which participants are to be fairly distributed among teams, where not only do the teams have preferences over the participants as in the canonical fair division setting, but the participants also have preferences over the teams. We focus on guaranteeing envy-freeness up to one participant (EF1) for the teams together with a stability condition for both sides. We show that an allocation satisfying EF1, swap stability, and individual stability always exists and can be computed in polynomial time, even when teams may have positive or negative values for participants. When teams have nonnegative values for participants, we prove that an EF1 and Pareto optimal allocation exists and, if the valuations are binary, can be found in polynomial time. We also show that an EF1 and justified envy-free allocation does not necessarily exist, and deciding whether such an allocation exists is computationally difficult.

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Publication Details

Journal
Games and Economic Behavior
Published
2024-08-22
DOI
https://doi.org/10.1016/j.geb.2024.07.008
Primary Topic
Game Theory and Voting Systems
Type
article
Field-Weighted Citation Impact
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article

Fair division with two-sided preferences

Yasushi Kawase, Hanna Sumita, Warut Suksompong, Ayumi Igarashi
Games and Economic Behavior
Game Theory and Voting Systems
article

Fair division with two-sided preferences

Yasushi Kawase, Hanna Sumita, Warut Suksompong, Ayumi Igarashi
article en

Abstract

We study a fair division setting in which participants are to be fairly distributed among teams, where not only do the teams have preferences over the participants as in the canonical fair division setting, but the participants also have preferences over the teams. We focus on guaranteeing envy-freeness up to one participant (EF1) for the teams together with a stability condition for both sides. We show that an allocation satisfying EF1, swap stability, and individual stability always exists and can be computed in polynomial time, even when teams may have positive or negative values for participants. When teams have nonnegative values for participants, we prove that an EF1 and Pareto optimal allocation exists and, if the valuations are binary, can be found in polynomial time. We also show that an EF1 and justified envy-free allocation does not necessarily exist, and deciding whether such an allocation exists is computationally difficult.

Games and Economic BehaviorVol. 147
Tokyo Institute of Technology (JP), National University of Singapore (SG), The University of Tokyo (JP)
Openalex Percentile: Top 83%
Game Theory and Voting Systems
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