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arxiv: 1806.00960 · v2 · pith:FBBMJGVFnew · submitted 2018-06-04 · 💻 cs.GT · cs.AI

The Capacity Constrained Facility Location problem

classification 💻 cs.GT cs.AI
keywords mechanismcapacitymechanismsconstrainedfacilityfamilyapproximationcharacterization
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We initiate the study of the capacity constrained facility location problem from a mechanism design perspective. The capacity constrained setting leads to a new strategic environment where a facility serves a subset of the population, which is endogenously determined by the ex-post Nash equilibrium of an induced subgame and is not directly controlled by the mechanism designer. Our focus is on mechanisms that are ex-post dominant-strategy incentive compatible (DIC) at the reporting stage. We provide a complete characterization of DIC mechanisms via the family of Generalized Median Mechanisms (GMMs). In general, the social welfare optimal mechanism is not DIC. Adopting the worst-case approximation measure, we attain tight lower bounds on the approximation ratio of any DIC mechanism. The well-known median mechanism is shown to be optimal among the family of DIC mechanisms for certain capacity ranges. Surprisingly, the framework we introduce provides a new characterization for the family of GMMs, and is responsive to gaps in the current social choice literature highlighted by Border and Jordan (1983) and Barbar{\`a}, Mass{\'o} and Serizawa (1998).

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  1. Strategyproof Mechanism for Two Heterogeneous Facilities with Constant Approximation Ratio

    cs.DS 2019-07 unverdicted novelty 6.0

    Designs a deterministic strategyproof mechanism for two-facility location on a line with optional agent preferences, achieving 2.75-approximation to social cost.