Truthful Facility Assignment with Resource Augmentation: An Exact Analysis of Serial Dictatorship
Ioannis Caragiannis, Aris Filos-Ratsikas, Soren Kristoffer Stiil, Frederiksen, Kristoffer Arnsfelt Hansen, Zihan Tan

TL;DR
This paper analyzes the performance of the Serial Dictatorship mechanism in truthful facility assignment problems under resource augmentation, providing exact bounds and showing improved ratios with increased capacity.
Contribution
It offers an exact linear programming analysis of Serial Dictatorship's worst-case performance with resource augmentation, deriving tight approximation bounds.
Findings
Serial Dictatorship's approximation ratio is g/(g-2) with capacity augmentation factor g ≥ 3.
Resource augmentation significantly improves the mechanism's approximation ratio.
As augmentation increases, the mechanism's performance approaches optimal.
Abstract
We study the truthful facility assignment problem, where a set of agents with private most-preferred points on a metric space are assigned to facilities that lie on the metric space, under capacity constraints on the facilities. The goal is to produce such an assignment that minimizes the social cost, i.e., the total distance between the most-preferred points of the agents and their corresponding facilities in the assignment, under the constraint of truthfulness, which ensures that agents do not misreport their most-preferred points. We propose a resource augmentation framework, where a truthful mechanism is evaluated by its worst-case performance on an instance with enhanced facility capacities against the optimal mechanism on the same instance with the original capacities. We study a very well-known mechanism, Serial Dictatorship, and provide an exact analysis of its performance.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAuction Theory and Applications · Optimization and Search Problems · Game Theory and Voting Systems
