Approximating Fair $k$-Min-Sum-Radii in Euclidean Space
Lukas Drexler, Annika Hennes, Abhiruk Lahiri, Melanie Schmidt, Julian, Wargalla

TL;DR
This paper develops a Polynomial Time Approximation Scheme (PTAS) for the fair $k$-min-sum-radii clustering problem in Euclidean spaces, addressing a gap in the literature for incorporating group fairness constraints.
Contribution
It introduces the first PTAS for fair $k$-min-sum-radii clustering in Euclidean spaces with constant $k$, extending existing algorithms to include group fairness constraints.
Findings
First PTAS for fair $k$-min-sum-radii clustering.
Applicable to multiple group fairness notions.
Works in Euclidean spaces of arbitrary dimension.
Abstract
The -center problem is a classical clustering problem in which one is asked to find a partitioning of a point set into clusters such that the maximum radius of any cluster is minimized. It is well-studied. But what if we add up the radii of the clusters instead of only considering the cluster with maximum radius? This natural variant is called the -min-sum-radii problem. It has become the subject of more and more interest in recent years, inspiring the development of approximation algorithms for the -min-sum-radii problem in its plain version as well as in constrained settings. We study the problem for Euclidean spaces of arbitrary dimension but assume the number of clusters to be constant. In this case, a PTAS for the problem is known (see Bandyapadhyay, Lochet and Saurabh, SoCG, 2023). Our aim is to extend the knowledge base for -min-sum-radii…
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Taxonomy
TopicsFacility Location and Emergency Management · Computational Geometry and Mesh Generation
MethodsBalanced Selection
