Constant-Approximate and Constant-Strategyproof Two-Facility Location
By: Elijah Journey Fullerton, Zeyuan Hu, C. Gregory Plaxton
Potential Business Impact:
Builds two places to help people fairly.
We study deterministic mechanisms for the two-facility location problem. Given the reported locations of n agents on the real line, such a mechanism specifies where to build the two facilities. The single-facility variant of this problem admits a simple strategyproof mechanism that minimizes social cost. For two facilities, however, it is known that any strategyproof mechanism is $\Omega(n)$-approximate. We seek to circumvent this strong lower bound by relaxing the problem requirements. Following other work in the facility location literature, we consider a relaxed form of strategyproofness in which no agent can lie and improve their outcome by more than a constant factor. Because the aforementioned $\Omega(n)$ lower bound generalizes easily to constant-strategyproof mechanisms, we introduce a second relaxation: Allowing the facilities (but not the agents) to be located in the plane. Our first main result is a natural mechanism for this relaxation that is constant-approximate and constant-strategyproof. A characteristic of this mechanism is that a small change in the input profile can produce a large change in the solution. Motivated by this observation, and also by results in the facility reallocation literature, our second main result is a constant-approximate, constant-strategyproof, and Lipschitz continuous mechanism.
Similar Papers
Truthful Two-Obnoxious-Facility Location Games with Optional Preferences and Minimum Distance Constraint
CS and Game Theory
Places bad things to make people tell truth.
Strategyproof Mechanisms for Facility Location with Prediction Under the Maximum Cost Objective
CS and Game Theory
Helps choose best places for things using smart guesses.
Truthful Facility Location with Candidate Locations and Limited Resources
CS and Game Theory
Helps pick the best place for services fairly.