Dynamic clustering to minimize the sum of radii Henzinger, Monika H ; https://orcid.org/0000-0002-5008-6530 Leniowski, Dariusz Mathieu, Claire In this paper, we study the problem of opening centers to cluster a set of clients in a metric space so as to minimize the sum of the costs of the centers and of the cluster radii, in a dynamic environment where clients arrive and depart, and the solution must be updated efficiently while remaining competitive with respect to the current optimal solution. We call this dynamic sum-of-radii clustering problem. We present a data structure that maintains a solution whose cost is within a constant factor of the cost of an optimal solution in metric spaces with bounded doubling dimension and whose worst-case update time is logarithmic in the parameters of the problem. Springer Nature 2020 info:eu-repo/semantics/article doc-type:article text http://purl.org/coar/resource_type/c_2df8fbb1 https://research-explorer.ista.ac.at/record/11674 Henzinger M, Leniowski D, Mathieu C. Dynamic clustering to minimize the sum of radii. <i>Algorithmica</i>. 2020;82(11):3183-3194. doi:<a href="https://doi.org/10.1007/s00453-020-00721-7">10.1007/s00453-020-00721-7</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1007/s00453-020-00721-7 info:eu-repo/semantics/altIdentifier/issn/0178-4617 info:eu-repo/semantics/altIdentifier/e-issn/1432-0541 info:eu-repo/semantics/altIdentifier/arxiv/1707.02577 info:eu-repo/semantics/openAccess