In this paper, we study the Pattern Avoidance problem of determining whether a given graph $G$ admits a linear vertex order which avoids a given pattern $P$, i.e., a vertex sequence with some forced and forbidden edges, on every suborder. Such patterns form a natural ordered counterpart to induced subgraphs in the order-invariant setting, and it is known that Pattern Avoidance captures a broad variety of graph problems including Bandwidth, Vertex Coloring, Queue Number, and extends to vertex-deletion problems such as Odd Cycle Transversal. We show that Pattern Avoidance is $\Sigma_2^{\textsf{P}}$-complete and furthermore remains intractable (in both the classical and parameterized sense) even under a variety of severe restrictions to both the pattern $P$ and the graph $G$. As our main contributions, we complement these lower bounds with the following tractability results, which provide a unifying framework for recognizing pattern-definable graph classes: - a fixed-parameter algorithm w.r.t. the vertex integrity of $G$ plus $|V(P)|$, - a fixed-parameter algorithm w.r.t. the neighborhood diversity of $G$ plus $|E(P)|$, and - a polynomial algorithm for Pattern Avoidance on forests for almost all constant-sized patterns.
Thomas Depian, S. D. Fink, Alexander Firbas et al.· 0 citations
This paper investigates the parameterized complexity of this problem and obtains an ETH-tight single-exponential algorithm for the classical unconstrained version of the problem, improving upon the previous $O^*(2^{k\cdot k})$ algorithms.
Alexander Firbas, R. Ganian, Sylvain Meunier et al.· arXiv.org· 0 citations
This paper proves that the former two problems are fixed-parameter tractable when parameterized by the treedepth of the input graph, and shows that Set of Degrees MST remains W[1]-hard parameterized by treedepth, even when combined with the feedback vertex number.
Narek Bojikian, Alexander Firbas, R. Ganian et al.· 0 citations
A comprehensive fine-grained complexity map of MCS on both unweighted and weighted graphs is developed and the results strictly delineate the algorithmic boundaries of consistent subset selection across diverse metric structures.
R. Ganian, M. Vasilakis, Simon Wietheger· arXiv.org· 0 citations
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