Improved Approximation Ratio for Strategyproof Facility Location on a Cycle
Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 4032-4039.
https://doi.org/10.24963/ijcai.2025/449
Keywords
- Game Theory and Economic Paradigms: GTEP: Mechanism design
- Multidisciplinary Topics and Applications: MTA: Economics
- Game Theory and Economic Paradigms: GTEP: Auctions and market-based systems
- Game Theory and Economic Paradigms: GTEP: Noncooperative games
Abstract
We study the problem of design of strategy-proof in expectation (SP) mechanisms for facility location on a cycle, with the objective of minimizing the sum of costs of n agents. We show that there exists an SP mechanism that attains an approximation ratio of 7/4 with respect to the sum of costs of the agents, thus improving the best known upper bound of 2 - 2/n in the cases of n ≥ 5. The mechanism obtaining the bound randomizes between two mechanisms known in the literature: the Random Dictator (RD) and the Proportional Circle Distance (PCD) mechanism of Meir (2019). To prove the result, we propose a cycle-cutting technique that allows for estimating the problem on a cycle by a problem on a line.
@inproceedings{ijcai2025p449,
title = {Improved Approximation Ratio for Strategyproof Facility Location on a Cycle},
author = {Rogowski, Krzysztof and Dziubiński, Marcin},
booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-25}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {James Kwok},
pages = {4032--4039},
year = {2025},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2025/449},
url = {https://doi.org/10.24963/ijcai.2025/449},
}
TY - CPAPER TI - Improved Approximation Ratio for Strategyproof Facility Location on a Cycle AU - Rogowski, Krzysztof AU - Dziubiński, Marcin T2 - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2025 SP - 4032 EP - 4039 DO - 10.24963/ijcai.2025/449 UR - https://doi.org/10.24963/ijcai.2025/449 ER -Copied
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