STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Greedy strikes back: improved facility location algorithms
Journal of Algorithms
An Improved Approximation Algorithm for the Metric Uncapacitated Facility Location Problem
Proceedings of the 9th International IPCO Conference on Integer Programming and Combinatorial Optimization
Building Steiner trees with incomplete global knowledge
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Hierarchical placement and network design problems
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Local Search Heuristics for k-Median and Facility Location Problems
SIAM Journal on Computing
Privacy Protection: p-Sensitive k-Anonymity Property
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Terminal backup, 3D matching, and covering cubic graphs
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
Region-restricted clustering for geographic data mining
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Efficient algorithms for the 2-gathering problem
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Efficient algorithms for the 2-gathering problem
ACM Transactions on Algorithms (TALG)
Minimizing movement in mobile facility location problems
ACM Transactions on Algorithms (TALG)
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We consider a min-max version of the previously studied r-gathering problem with unit-demands. The problem we consider is a metric facility-location problem, in which each open facility must serve at least r customers, and the maximum of all the facility and connection costs should be minimized (rather than their sum). This problem is motivated by scenarios in which r customers are required for a facility to be worth opening, and the costs represent the time until the facility/connection will be available (i.e., we want to have the complete solution ready as soon as possible). We present a 3-approximation algorithm for this problem, and prove that it cannot be approximated better (assuming P ≠ NP). Next we consider this problem with the additional natural requirement that each customer will be assigned to a nearest open facility, and present a 9-approximation algorithm. We further consider previously introduced special cases and variants, and obtain improved algorithmic and hardness results.