Mechanism Design for Constrained Heterogeneous Facility Location

Author(s):  
Maria Kyropoulou ◽  
Carmine Ventre ◽  
Xiaomeng Zhang
Author(s):  
Hau Chan ◽  
Aris Filos-Ratsikas ◽  
Bo Li ◽  
Minming Li ◽  
Chenhao Wang

The study of approximate mechanism design for facility location has been in the center of research at the intersection of artificial intelligence and economics for the last decade, largely due to its practical importance in various domains, such as social planning and clustering. At a high level, the goal is to select a number of locations on which to build a set of facilities, aiming to optimize some social objective based on the preferences of strategic agents, who might have incentives to misreport their private information. This paper presents a comprehensive survey of the significant progress that has been made since the introduction of the problem, highlighting all the different variants and methodologies, as well as the most interesting directions for future research.


2020 ◽  
Vol 34 (02) ◽  
pp. 1806-1813 ◽  
Author(s):  
Haris Aziz ◽  
Hau Chan ◽  
Barton Lee ◽  
Bo Li ◽  
Toby Walsh

We consider the facility location problem in the one-dimensional setting where each facility can serve a limited number of agents from the algorithmic and mechanism design perspectives. From the algorithmic perspective, we prove that the corresponding optimization problem, where the goal is to locate facilities to minimize either the total cost to all agents or the maximum cost of any agent is NP-hard. However, we show that the problem is fixed-parameter tractable, and the optimal solution can be computed in polynomial time whenever the number of facilities is bounded, or when all facilities have identical capacities. We then consider the problem from a mechanism design perspective where the agents are strategic and need not reveal their true locations. We show that several natural mechanisms studied in the uncapacitated setting either lose strategyproofness or a bound on the solution quality %on the returned solution for the total or maximum cost objective. We then propose new mechanisms that are strategyproof and achieve approximation guarantees that almost match the lower bounds.


Author(s):  
Xujin Chen ◽  
Xiaodong Hu ◽  
Xiaohua Jia ◽  
Minming Li ◽  
Zhongzheng Tang ◽  
...  

2021 ◽  
pp. 49-63
Author(s):  
Aris Filos-Ratsikas ◽  
Alexandros A. Voudouris

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