Simultaneous Feedback Edge Set: A Parameterized Perspective

TL;DR

This paper studies the computational complexity of the Simultaneous Feedback Edge Set problem, providing hardness results, fixed-parameter algorithms, and kernelization, along with exploring a related maximum acyclic subgraph problem.

Contribution

It establishes NP-hardness for -color case, develops an FPT algorithm with exponential dependence on parameters, and introduces a polynomial kernelization for the problem.

Findings

NP-hardness for -color case via reduction from Vertex Cover

FPT algorithm with runtime O(2^{k+ ext{log} k} n^{O(1)})

Polynomial kernel with (k)^{O()} vertices

Abstract

In this paper we consider Simultaneous Feedback Edge Set (Sim-FES) problem. In this problem, the input is an $n$-vertex graph $G$, an integer $k$ and a coloring function ${\sf col}: E(G) \rightarrow 2^{[\alpha]}$ and the objective is to check whether there is an edge subset $S$ of cardinality at most $k$ in $G$ such that for all $i \in [\alpha]$, $G_i - S$ is acyclic. Here, $G_i=(V(G), \{e\in E(G) \mid i \in {\sf col}(e)\})$ and $[\alpha]=\{1,\ldots,\alpha\}$. When $\alpha =1$, the problem is polynomial time solvable. We show that for $\alpha =3$ Sim-FES is NP-hard by giving a reduction from Vertex Cover on cubic graphs. The same reduction shows that the problem does not admit an algorithm of running time $O(2^{o(k)}n^{O(1)})$ unless ETH fails. This hardness result is complimented by an FPT algorithm for Sim-FES running in time $O(2^{\omega k\alpha+\alpha \log k} n^{O(1)})$, where $\omega$ is the exponent in the running time of matrix multiplication. The same algorithm gives a polynomial time algorithm for the case when $\alpha =2$. We also give a kernel for Sim-FES with $(k\alpha)^{O(\alpha)}$ vertices. Finally, we consider the problem Maximum Simultaneous Acyclic Subgraph. Here, the input is a graph $G$, an integer $q$ and, a coloring function ${\sf col}: E(G) \rightarrow 2^{[\alpha]}$. The question is whether there is a edge subset $F$ of cardinality at least $q$ in $G$ such that for all $i\in [\alpha]$, $G[F_i]$ is acyclic. Here, $F_i=\{e \in F \mid i \in \textsf{col}(e)\}$. We give an FPT algorithm for running in time $O(2^{\omega q \alpha}n^{O(1)})$.