In the Universal Facility Location problem we are given a set of demand points and a set of facilities. The goal is to assign the demands to facilities in such a way that the sum of service and facility costs is minimized. The service cost is proportional to the distance each unit of demand has to travel to its assigned facility, whereas the facility cost of each facility i depends on the amount of demand assigned to that facility and is given by a cost function fi(·). We present a (7.88 + ε)-approximation algorithm for the Universal Facility Location problem based on local search, under the assumption that the cost functions fi are nondecreasing. The algorithm chooses local improvement steps by solving a knapsack-like subproblem using dynamic programming. This is the first constant-factor approximation algorithm for this problem. Our algorithm also slightly improves the best known approximation ratio for the capacitated facility location problem with non-uniform hard capacities. © Springer-Verlag 2003.
CITATION STYLE
Mahdian, M., & Pá, M. (2003). Universal Facility Location. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2832, 409–421. https://doi.org/10.1007/978-3-540-39658-1_38
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