Parameterized mixed cluster editing via modular decomposition
Maise Dantas da Silva, F\'abio Protti, Jayme Luiz Szwarcfiter

TL;DR
This paper introduces a generalized graph editing problem called Mixed Cluster Editing, focusing on transforming graphs into unions of complete or complete bipartite graphs, and provides a linear-time kernelization algorithm for a specific case using modular decomposition.
Contribution
It generalizes existing cluster editing problems and develops a linear-time kernelization algorithm for the ${ m L}$-Cluster Editing problem using modular decomposition techniques.
Findings
Presented a linear-time algorithm for kernelization.
Extended cluster editing to mixed cluster graphs.
Analyzed fixed-parameter tractability of the problem.
Abstract
In this paper we introduce a natural generalization of the well-known problems Cluster Editing and Bicluster Editing, whose parameterized versions have been intensively investigated in the recent literature. The generalized problem, called Mixed Cluster Editing or -Cluster Editing, is formulated as follows. Let be a family of graphs. Given a graph and a nonnegative integer , transform , through a sequence of at most edge editions, into a target graph with the following property: is a vertex-disjoint union of graphs such that every is a member of . The graph is called a mixed cluster graph or -cluster graph. Let denote the family of complete graphs, the family of complete -partite graphs (), and . In this work we focus on the case…
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Taxonomy
TopicsAdvanced Graph Theory Research · Optimization and Search Problems · DNA and Biological Computing
