Effective data reduction for strongly stable matching in very sparse graphs

We provide a linear-time computable problem kernel of linear size for Strongly Stable Roommates parameterized by the feedback edge number of the acceptability graph (which encodes which agents may be matched to each other). • A linear problem kernel for Strongly Stable Matching is provided. • Stability of a matching is sensible to vertex/edge deletion. • Introduction of annotated problem version helps to design reduction rules.

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Publication Details

Journal
Information Processing Letters
Published
2024-10-16
DOI
https://doi.org/10.1016/j.ipl.2024.106534
Primary Topic
Complexity and Algorithms in Graphs
Type
article
Field-Weighted Citation Impact
0.00

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article

Effective data reduction for strongly stable matching in very sparse graphs

André Nichterlein, Klaus Heeger, R. Wolf
Information Processing Letters
Complexity and Algorithms in Graphs
article

Effective data reduction for strongly stable matching in very sparse graphs

André Nichterlein, Klaus Heeger, R. Wolf
article en

Abstract

We provide a linear-time computable problem kernel of linear size for Strongly Stable Roommates parameterized by the feedback edge number of the acceptability graph (which encodes which agents may be matched to each other). • A linear problem kernel for Strongly Stable Matching is provided. • Stability of a matching is sensible to vertex/edge deletion. • Introduction of annotated problem version helps to design reduction rules.

Information Processing LettersVol. 188
Technische Universität Berlin (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 78%
Complexity and Algorithms in Graphs
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