Efficient and Stable Fully Dynamic Facility Location
Sayan Bhattacharya, Silvio Lattanzi, Nikos Parotsidis
Abstract
We consider the classic facility location problem in fully dynamic data streams, where elements can be both inserted and deleted. In this problem, one is interested in maintaining a stable and high quality solution throughout the data stream while using only little time per update (insertion or deletion). We study the problem and provide the first algorithm that at the same time maintains a constant approximation and incurs polylogarithmic amortized recourse per update. We complement our theoretical results with an experimental analysis showing the practical efficiency of our method.
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Install the CLIlune papers fulltext e0e1f4b3-24ee-4e4d-89af-3a284f693e48Cited by top-tier papers12
- Fully Dynamic k-Clustering in Õ(k) Update TimeSayan Bhattacharya, Martín Costa, Silvio Lattanzi, Nikos ParotsidisNeurIPS 2023 · 10 citations
- Fully Dynamic k-Median with Near-Optimal Update Time and RecourseSayan Bhattacharya, Martín Costa, Ermiya FarokhnejadSTOC 2025 · 9 citations
- Chasing Positive BodiesSayan Bhattacharya, Niv Buchbinder, Roie Levin, Thatchaphol SaranurakFOCS 2023 · 6 citations
- Dynamic algorithms for k-center on graphsEmilio Cruciani, Sebastian Forster, Gramoz Goranci, Yasamin Nazari et al.SODA 2024 · 4 citations
- Dynamic Facility Location in High Dimensional Euclidean SpacesSayan Bhattacharya, Gramoz Goranci, Shaofeng H.-C. Jiang, Yi Qian et al.ICML 2024 · 3 citations
Builds on2
- Fully Dynamic Algorithm for Constrained Submodular OptimizationSilvio Lattanzi, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakub Tarnawski et al.NeurIPS 2020 · 30 citations
- Consistent k-Clustering for General MetricsHendrik Fichtenberger, Silvio Lattanzi, Ashkan Norouzi-Fard, Ola SvenssonSODA 2021 · 7 citations
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