Multi-Stage Facility Location Problems with Transient Agents


  • Xuezhen Wang City University of Hong Kong
  • Vincent Chau Southeast University
  • Hau Chan University of Nebraska-Lincoln
  • Ken C.K. Fong Lingnan University
  • Minming Li City University of Hong Kong



GTEP: Social Choice / Voting, GTEP: Game Theory, GTEP: Mechanism Design, MAS: Mechanism Design


We study various models for the one-dimensional multi-stage facility location problems with transient agents, where a transient agent arrives in some stage and stays for a number of consecutive stages. In the problems, we need to serve each agent in one of their stages by determining the location of the facility at each stage. In the first model, we assume there is no cost for moving the facility across the stages. We focus on optimal algorithms to minimize both the social cost objective, defined as the total distance of all agents to the facility over all stages, and the maximum cost objective, defined as the max distance of any agent to the facility over all stages. For each objective, we give a slice-wise polynomial (XP) algorithm (i.e., solvable in m^f(k) for some fixed parameter k and computable function f, where m is the input size) and show that there is a polynomial-time algorithm when a natural first-come-first-serve (FCFS) order of agent serving is enforced. We then consider the mechanism design problem, where the agents' locations and arrival stages are private, and design a group strategy-proof mechanism that achieves good approximation ratios for both objectives and settings with and without FCFS ordering. In the second model, we consider the facility's moving cost between adjacent stages under the social cost objective, which accounts for the total moving distance of the facility. Correspondingly, we design XP (and polynomial time) algorithms and a group strategy-proof mechanism for settings with or without the FCFS ordering.




How to Cite

Wang, X., Chau, V., Chan, H., Fong, K. C., & Li, M. (2023). Multi-Stage Facility Location Problems with Transient Agents. Proceedings of the AAAI Conference on Artificial Intelligence, 37(5), 5850-5857.



AAAI Technical Track on Game Theory and Economic Paradigms