The problem of computing a $2$-T-connected spanning subgraph with minimum number of edges in directed graphs
September 29, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Raed Jaberi, Reham Mansour
arXiv ID
2409.19773
Category
cs.DS: Data Structures & Algorithms
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Let $G=(V,E)$ be a strongly connected graph with $|V|\geq 3$. For $T\subseteq V$, the strongly connected graph $G$ is $2$-T-connected if $G$ is $2$-edge-connected and for each vertex $w$ in $T$, $w$ is not a strong articulation point. This concept generalizes the concept of $2$-vertex connectivity when $T$ contains all the vertices in $G$. This concept also generalizes the concept of $2$-edge connectivity when $|T|=0$. The concept of $2$-T-connectivity was introduced by Durand de Gevigney and Szigeti in $2018$. In this paper, we prove that there is a polynomial-time 4-approximation algorithm for the following problem: given a $2$-T-connected graph $G=(V,E)$, identify a subset $E^ {2T} \subseteq E$ of minimum cardinality such that $(V,E^{2T})$ is $2$-T-connected.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Data Structures & Algorithms
π
π
The Cartographer
R.I.P.
π»
Ghosted
Route Planning in Transportation Networks
R.I.P.
π»
Ghosted
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
R.I.P.
π»
Ghosted
Hierarchical Clustering: Objective Functions and Algorithms
R.I.P.
π»
Ghosted
Graph Isomorphism in Quasipolynomial Time
π
π
The Cartographer
Simulation optimization: A review of algorithms and applications
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted