Facility Location Games for Multi-Location Agents with Satisfaction

TL;DR

This paper designs strategy-proof mechanisms for multi-location agent facility location games, optimizing satisfaction functions under various objectives, with proven approximation ratios and bounds for both desirable and obnoxious settings.

Contribution

It introduces new group strategy-proof mechanisms with tight approximation ratios for multi-location agents, advancing the understanding of truthful facility location design.

Findings

Proposed mechanisms with approximation ratios of 2 and 5/4 for desirable games.

Established optimality of mechanisms with ratio 2 for obnoxious games.

Derived lower bounds for randomized strategy-proof mechanisms.

Abstract

In this paper, we study mechanism design for single-facility location games where each agent has multiple private locations in [0, 1]. The individual objective is a satisfaction function that measures the discrepancy between the optimal facility location for an agent and the location provided by the mechanism. Based on different distance functions from agents to the facility, we consider two types of individual objectives: the sum-variant satisfaction and the max-variant satisfaction. Our goal is to design mechanisms that locate one facility to maximize the sum (or the minimum) of all agents' satisfactions, while incentivizing agents to truthfully report their locations. In this paper, we mainly focus on desirable and obnoxious facility location games. For desirable facility location games, we propose two group strategy-proof mechanisms with approximation ratios of 2 and 5/4 for maximizing the sum of the sum-variant and max-variant satisfaction, respectively. Moreover, another mechanism achieves an approximation ratio of 2 for simultaneously maximizing the minimum of the sum-variant satisfaction and the minimum of the max-variant satisfaction. For obnoxious facility location games, we establish that two group strategy-proof mechanisms are the best possible, providing an approximation ratio of 2 for maximizing the sum of the sum-variant satisfaction and the sum of the max-variant satisfaction, respectively. Additionally, we devise two 4/3-approximation randomized group strategy-proof mechanisms, and provide two lower bounds of 1.0625 and 1.0448 of randomized strategy-proof mechanisms for maximizing the sum of the sum-variant satisfaction and the sum of the max-variant satisfaction, respectively.