TY - GEN
T1 - Facility Location Problems with Capacity Constraints
T2 - 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
AU - Auricchio, Gennaro
AU - Wang, Zihe
AU - Zhang, Jie
PY - 2024/8/9
Y1 - 2024/8/9
N2 - In this paper, we investigate the Mechanism Design aspects of the m-Capacitated Facility Location Problem (m-CFLP) on a line.We focus on two frameworks.In the first framework, the number of facilities is arbitrary, all facilities have the same capacity, and the number of agents is equal to the total capacity of all facilities.In the second framework, we aim to place two facilities, each with a capacity of at least half of the total agents.For both of these frameworks, we propose truthful mechanisms with bounded approximation ratios with respect to the Social Cost (SC) and the Maximum Cost (MC).When m > 2, the result sharply contrasts with the impossibility results known for the classic m-Facility Location Problem, where capacity constraints are not considered.Furthermore, all our mechanisms are optimal with respect to the MC and optimal or nearly optimal with respect to the SC among anonymous mechanisms.For both frameworks, we provide a lower bound on the approximation ratio that any truthful and deterministic mechanism can achieve with respect to the SC and MC.
AB - In this paper, we investigate the Mechanism Design aspects of the m-Capacitated Facility Location Problem (m-CFLP) on a line.We focus on two frameworks.In the first framework, the number of facilities is arbitrary, all facilities have the same capacity, and the number of agents is equal to the total capacity of all facilities.In the second framework, we aim to place two facilities, each with a capacity of at least half of the total agents.For both of these frameworks, we propose truthful mechanisms with bounded approximation ratios with respect to the Social Cost (SC) and the Maximum Cost (MC).When m > 2, the result sharply contrasts with the impossibility results known for the classic m-Facility Location Problem, where capacity constraints are not considered.Furthermore, all our mechanisms are optimal with respect to the MC and optimal or nearly optimal with respect to the SC among anonymous mechanisms.For both frameworks, we provide a lower bound on the approximation ratio that any truthful and deterministic mechanism can achieve with respect to the SC and MC.
UR - http://www.scopus.com/inward/record.url?scp=85203135253&partnerID=8YFLogxK
U2 - 10.24963/ijcai.2024/293
DO - 10.24963/ijcai.2024/293
M3 - Chapter in a published conference proceeding
AN - SCOPUS:85203135253
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 2651
EP - 2659
BT - Proceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
A2 - Larson, Kate
PB - International Joint Conferences on Artificial Intelligence
Y2 - 3 August 2024 through 9 August 2024
ER -