Title
Approximation algorithms for clustering with dynamic points
Abstract
We study two generalizations of classic clustering problems called dynamic ordered k-median and dynamic k-supplier, where the points that need clustering evolve over time, and we are allowed to move the cluster centers between consecutive time steps. In these dynamic clustering problems, the general goal is to minimize certain combinations of the service cost of points and the movement cost of centers, or to minimize one subject to some constraints on the other. We obtain a constant-factor approximation algorithm for dynamic ordered k-median under mild assumptions on the input. We give a 3-approximation for dynamic k-supplier and a multi-criteria approximation for its outlier version where some points can be discarded, when the number of time steps is two. We complement the algorithms with almost matching hardness results.
Year
DOI
Venue
2022
10.1016/j.jcss.2022.07.001
Journal of Computer and System Sciences
Keywords
DocType
Volume
Clustering,Facility location,Dynamic points,Multi-objective optimization,Approximation algorithms
Journal
130
ISSN
Citations 
PageRank 
0022-0000
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Shichuan Deng100.34
Jian Li281152.97
Yuval Rabani32265274.98