FPT approximations for Capacitated Sum of Radii and Diameters

Fuente: arXiv
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Autores principales: Filtser, Arnold, Gadekar, Ameet
Formato: Preprint
Publicado: 2024
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author Filtser, Arnold
Gadekar, Ameet
author_facet Filtser, Arnold
Gadekar, Ameet
contents The Capacitated Sum of Radii problem involves partitioning a set of points $P$, where each point $p\in P$ has capacity $U_p$, into $k$ clusters that minimize the sum of cluster radii, such that the number of points in the cluster centered at point $p$ is at most $U_p$. We begin by showing that the problem is APX-hard, and that under gap-ETH there is no parameterized approximation scheme (FPT-AS). We then construct a $\approx5.83$-approximation algorithm in FPT time (improving a previous $\approx7.61$ approximation in FPT time). Our results also hold when the objective is a general monotone symmetric norm of radii. We also improve the approximation factors for the uniform capacity case, and for the closely related problem of Capacitated Sum of Diameters.
format Preprint
id arxiv_https___arxiv_org_abs_2409_04984
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle FPT approximations for Capacitated Sum of Radii and Diameters
Filtser, Arnold
Gadekar, Ameet
Data Structures and Algorithms
The Capacitated Sum of Radii problem involves partitioning a set of points $P$, where each point $p\in P$ has capacity $U_p$, into $k$ clusters that minimize the sum of cluster radii, such that the number of points in the cluster centered at point $p$ is at most $U_p$. We begin by showing that the problem is APX-hard, and that under gap-ETH there is no parameterized approximation scheme (FPT-AS). We then construct a $\approx5.83$-approximation algorithm in FPT time (improving a previous $\approx7.61$ approximation in FPT time). Our results also hold when the objective is a general monotone symmetric norm of radii. We also improve the approximation factors for the uniform capacity case, and for the closely related problem of Capacitated Sum of Diameters.
title FPT approximations for Capacitated Sum of Radii and Diameters
topic Data Structures and Algorithms
url https://arxiv.org/abs/2409.04984