
Mechanism Design for TwoOppositeFacility Location Games with Penalties on Distance
This paper is devoted to the twooppositefacility location games with a...
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Strategyproof Facility Location in Perturbation Stable Instances
We consider kFacility Location games, where n strategic agents report t...
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Manipulationresistant facility location mechanisms for ZVline graphs
In many reallife scenarios, a group of agents needs to agree on a commo...
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GroupStrategyproof mechanisms for facility location with Euclidean distance
We characterize the class of groupstrategyproof mechanisms for single f...
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Strategy Proof Mechanisms for Facility Location with Capacity Limits
An important feature of many real world facility location problems are c...
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Delegated Stochastic Probing
Delegation covers a broad class of problems in which a principal doesn't...
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Mechanism Design for Locating a Facility under Partial Information
We study the classic mechanism design problem of locating a public facil...
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Heterogeneous Facility Location Games
We study heterogeneous kfacility location games. In this model there are k facilities where each facility serves a different purpose. Thus, the preferences of the agents over the facilities can vary arbitrarily. Our goal is to design strategy proof mechanisms that place the facilities in a way to maximize the minimum utility among the agents. For k=1, if the agents' locations are known, we prove that the mechanism that places the facility on an optimal location is strategy proof. For k ≥ 2, we prove that there is no optimal strategy proof mechanism, deterministic or randomized, even when k=2 there are only two agents with known locations, and the facilities have to be placed on a line segment. We derive inapproximability bounds for deterministic and randomized strategy proof mechanisms. Finally, we focus on the line segment and provide strategy proof mechanisms that achieve constant approximation. All of our mechanisms are simple and communication efficient. As a byproduct we show that some of our mechanisms can be used to achieve constant factor approximations for other objectives as the social welfare and the happiness.
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