Fair Vertex Problems Parameterized by Cluster Vertex Deletion
Tom\'a\v{s} Masa\v{r}\'ik, J\k{e}drzej Olkowski, Anna Zych-Pawlewicz

TL;DR
This paper investigates the parameterized complexity of fair MSO$_1$ problems based on cluster vertex deletion, demonstrating W[1]-hardness in general but providing conditions for fixed-parameter tractability for various graph problems.
Contribution
It proves W[1]-hardness of fair MSO$_1$ problems parameterized by cluster vertex deletion and offers a sufficient condition for fixed-parameter tractability in this setting.
Findings
W[1]-hardness demonstrated for general case
FPT algorithms provided under specific conditions
Solved Fair [σ,ρ]-Domination for finite or cofinite σ and ρ
Abstract
In this paper we study fair variants of MSO definable problems parameterized by cluster vertex deletion number, i.e., the smallest number of vertices required to be removed from the graph such that what remains is a collection of cliques. While typical graph problems seek the smallest set of vertices satisfying some property, their fair variants seek such a set that does not contain too many vertices in any neighborhood of any vertex. Formally, the task is to find a set satisfying some MSO definable property, whose fair cost is at most , i.e., such that for all it holds that . Recently, Knop, Masa\v{r}\'ik, and Toufar [MFCS 2019] showed that all fair MSO definable problems can be solved in FPT time parameterized by the twin cover of a graph. They asked whether such a statement can be achieved for a more general…
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