Approximating $δ$-Covering
August 08, 2024 · Declared Dead · 🏛 Workshop on Approximation and Online Algorithms
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Tim A. Hartmann, Tom Janßen
arXiv ID
2408.04517
Category
cs.DS: Data Structures & Algorithms
Citations
3
Venue
Workshop on Approximation and Online Algorithms
Last Checked
4 months ago
Abstract
$δ$-Covering, for some covering range $δ>0$, is a continuous facility location problem on undirected graphs where all edges have unit length. The facilities may be positioned on the vertices as well as on the interior of the edges. The goal is to position as few facilities as possible such that every point on every edge has distance at most $δ$ to one of these facilities. For large $δ$, the problem is similar to dominating set, which is hard to approximate, while for small $δ$, say close to $1$, the problem is similar to vertex cover. In fact, as shown by Hartmann et al. [Math. Program. 22], $δ$-Covering for all unit-fractions $δ$ is polynomial time solvable, while for all other values of $δ$ the problem is NP-hard. We study the approximability of $δ$-Covering for every covering range $δ>0$. For $δ\geq 3/2$, the problem is log-APX-hard, and allows an $\mathcal O(\log n)$ approximation. For every $δ< 3/2$, there is a constant factor approximation of a minimum $δ$-cover (and the problem is APX-hard when $δ$ is not a unit-fraction). We further study the dependency of the approximation ratio on the covering range $δ< 3/2$. By providing several polynomial time approximation algorithms and lower bounds under the Unique Games Conjecture, we narrow the possible approximation ratio, especially for $δ$ close to the polynomial time solvable cases.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Data Structures & Algorithms
📚
📚
The Cartographer
R.I.P.
👻
Ghosted
Route Planning in Transportation Networks
R.I.P.
👻
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
👻
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
👻
Ghosted
Graph Isomorphism in Quasipolynomial Time
📚
📚
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
👻
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
👻
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
👻
Ghosted