Mechanism Design for Facility Location Problems: A Survey

Chan, Hau; Filos-Ratsikas, Aris; Li, Bo; Li, Minming; Wang, Chenhao

doi:10.24963/ijcai.2021/596

Cited by 36 publications

(7 citation statements)

References 11 publications

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“…Indicatively, different variants have been considered depending on the number of facilities to locate [Lu et al, 2010, Fotakis andTzamos, 2014], whether the facilities are desirable or obnoxious [Cheng et al, 2013], whether the preferences of the agents are homogeneous or heterogeneous [Feigenbaum and Sethuraman, 2015, Serafino and Ventre, 2016, Kanellopoulos et al, 2023a, Deligkas et al, 2023, Chen et al, 2020, and whether there are constraints about where the facilities can be placed [Feldman et al, 2016, Kanellopoulos et al, 2023b, Xu et al, 2021 in combination with min or sum individual costs. For a detailed exposition of the truthful facility location literature, we refer the interest reader to the survey of Chan et al [2021].…”

Section: Other Related Workmentioning

confidence: 99%

Constrained heterogeneous facility location games with max-variant cost

et al. 2023

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We consider a problem where agents have private positions on a line, and public approval preferences over two facilities, and their cost is the maximum distance from their approved facilities.e goal is to decide the facility locations to minimize the total and the max cost, while incentivizing the agents to be truthful. We design a strategyproof mechanism that is simultaneously 11and 5-approximate for these two objective functions, thus improving the previously best-known bounds of 2n + 1 and 9.

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Section: Other Related Workmentioning

confidence: 99%

Constrained heterogeneous facility location games with max-variant cost

et al. 2023

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“…The problem we tackle here is also related to facility location, a problem with attracted substantial interest by the computational social choice and mechanism design community. For a recent survey, see Chan et al [13].…”

Section: Further Related Workmentioning

confidence: 99%

Truthful Aggregation of Budget Proposals with Proportionality Guarantees

Caragiannis¹,

Christodoulou²,

Protopapas³

2022

Preprint

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We study a participatory budgeting problem, where a set of strategic agents wish to split a divisible budget among different projects, by aggregating their proposals on a single division. Unfortunately, the straight-forward rule that divides the budget proportionally is susceptible to manipulation. In a recent work, Freeman et al. [16] proposed a class of truthful mechanisms, called moving phantom mechanisms. Among others, they propose a proportional mechanism, in the sense that in the extreme case where all agents prefer a single project to receive the whole amount, the budget is assigned proportionally.While proportionality is a naturally desired property, it is defined over a limited type of preference profiles. To address this, we expand the notion of proportionality, by proposing a quantitative framework which evaluates a budget aggregation mechanism according to its worst-case distance from the proportional allocation. Crucially, this is defined for every preference profile. We study this measure on the class of moving phantom mechanisms, and we provide approximation guarantees. For two projects, we show that the Uniform Phantom mechanism is the optimal among all truthful mechanisms. For three projects, we propose a new, proportional mechanism which is virtually optimal among all moving phantom mechanisms. Finally, we provide impossibility results regarding the approximability of moving phantom mechanisms.

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“…There have since been many extensions of facility location mechanism design that build off these results, such as the placement of multiple facilities by Miyagawa [25,26] and Fotakis and Tzamos [18], as well as when agents have fractional or optional preferences [16,10]. For further related work, we refer the reader to a survey by Chan et al [9]. A connection between voting and facility location problems is drawn by Feldman et al [15], in which mechanisms minimizing social cost are formulated for the problem where there is a fixed, limited set of candidates on the real line.…”

Section: Related Workmentioning

confidence: 99%

Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism

Aziz¹,

Lam²,

Suzuki³

et al. 2022

Preprint

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Proportionality is an attractive fairness concept that has been applied to a range of problems including the facility location problem, a classic problem in social choice. In our work, we propose a concept called Strong Proportionality, which ensures that when there are two groups of agents at different locations, both groups incur the same total cost. We show that although Strong Proportionality is a well-motivated and basic axiom, there is no deterministic strategyproof mechanism satisfying the property. We then identify a randomized mechanism called Random Rank (which uniformly selects a number k between 1 to n and locates the facility at the k'th highest agent location) which satisfies Strong Proportionality in expectation. Our main theorem characterizes Random Rank as the unique mechanism that achieves universal truthfulness, universal anonymity, and Strong Proportionality in expectation among all randomized mechanisms. Finally, we show via the AverageOrRandomRank mechanism that even stronger ex-post fairness guarantees can be achieved by weakening universal truthfulness to strategyproofness in expectation.

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Mechanism Design for Facility Location Problems: A Survey

Cited by 36 publications

References 11 publications

Constrained heterogeneous facility location games with max-variant cost

Constrained heterogeneous facility location games with max-variant cost

Truthful Aggregation of Budget Proposals with Proportionality Guarantees

Random Rank: The One and Only Strategyproof and Proportionally Fair Randomized Facility Location Mechanism

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