Reducing Dominating Sets in Graphs

Fuente: arXiv
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Autori principali: Inza, Ernesto Parra, Almira, José María Sigarreta, Vakhania, Nodari
Natura: Preprint
Pubblicazione: 2024
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author Inza, Ernesto Parra
Almira, José María Sigarreta
Vakhania, Nodari
author_facet Inza, Ernesto Parra
Almira, José María Sigarreta
Vakhania, Nodari
contents A dominating set of a graph $G=(V,E)$ is a subset of vertices $S\subseteq V$ such that every vertex $v\in V\setminus S$ has at least one neighbor in set $S$. The corresponding optimization problem is known to be NP-hard. The best known polynomial time approximation algorithm for the problem separates the solution process in two stages applying first a fast greedy algorithm to obtain an initial dominating set, and then it uses an iterative procedure to reduce (purify) this dominating set. The purification stage turned out to be practically efficient. Here we further strengthen the purification stage presenting four new purification algorithms. All four purification procedures outperform the earlier purification procedure. The algorithms were tested for over 1300 benchmark problem instances. Compared to the known upper bounds, the obtained solutions were about 7 times better. Remarkably, for the 500 benchmark instances for which the optimum is known, the optimal solutions were obtained for 46.33\% of the tested instances, whereas the average error for the remaining instances was about 1.01.
format Preprint
id arxiv_https___arxiv_org_abs_2404_18028
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reducing Dominating Sets in Graphs
Inza, Ernesto Parra
Almira, José María Sigarreta
Vakhania, Nodari
Discrete Mathematics
68R10, 05C69, 90C59
A dominating set of a graph $G=(V,E)$ is a subset of vertices $S\subseteq V$ such that every vertex $v\in V\setminus S$ has at least one neighbor in set $S$. The corresponding optimization problem is known to be NP-hard. The best known polynomial time approximation algorithm for the problem separates the solution process in two stages applying first a fast greedy algorithm to obtain an initial dominating set, and then it uses an iterative procedure to reduce (purify) this dominating set. The purification stage turned out to be practically efficient. Here we further strengthen the purification stage presenting four new purification algorithms. All four purification procedures outperform the earlier purification procedure. The algorithms were tested for over 1300 benchmark problem instances. Compared to the known upper bounds, the obtained solutions were about 7 times better. Remarkably, for the 500 benchmark instances for which the optimum is known, the optimal solutions were obtained for 46.33\% of the tested instances, whereas the average error for the remaining instances was about 1.01.
title Reducing Dominating Sets in Graphs
topic Discrete Mathematics
68R10, 05C69, 90C59
url https://arxiv.org/abs/2404.18028