2020
DOI: 10.1007/978-3-030-58150-3_44
|View full text |Cite
|
Sign up to set email alerts
|

Approximating Maximum Acyclic Matchings by Greedy and Local Search Strategies

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2025
2025

Publication Types

Select...
3
2
1

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…This result contrasts with a result by Kobler and Rotics [20] that deciding if the size of the maximum induced matching of G is equal to the size of the maximum matching is polynomially solvable for general graphs. Also, Furst and Rautenbach et al [3] proved that every graph with n vertices, the maximum degree ∆, and no isolated vertex, has an acyclic matching of size at least (1 − o ∆ (1)) 6n/∆ 2 , and they explained how to find such an acyclic matching in polynomial time. Moreover, they provided a (2∆ + 2)/3-approximation algorithm for the Acyclic Matching problem, based on greedy and local search strategies.…”
Section: Introductionmentioning
confidence: 99%
“…This result contrasts with a result by Kobler and Rotics [20] that deciding if the size of the maximum induced matching of G is equal to the size of the maximum matching is polynomially solvable for general graphs. Also, Furst and Rautenbach et al [3] proved that every graph with n vertices, the maximum degree ∆, and no isolated vertex, has an acyclic matching of size at least (1 − o ∆ (1)) 6n/∆ 2 , and they explained how to find such an acyclic matching in polynomial time. Moreover, they provided a (2∆ + 2)/3-approximation algorithm for the Acyclic Matching problem, based on greedy and local search strategies.…”
Section: Introductionmentioning
confidence: 99%