Jacob, Ashwin and Panolan, Fahad
(2020)
Structural Parameterizations with Modulator Oblivion.
arXiv.org.
Abstract
It is known that problems like Vertex Cover, Feedback Vertex Set and Odd Cycle Transversal are polynomial time solvable in the class of chordal graphs. We consider these problems in a graph that has at most k vertices whose deletion results in a chordal graph, when parameterized by k. While this investigation fits naturally into the recent trend of what are called ‘structural parameterizations’, here we assume that the deletion set is not given. One method to solve them is to compute a k-sized or an approximate (f(k) sized, for a function f) chordal vertex deletion set and then use the structural properties of the graph to design an algorithm. This method leads to at least k O(k)n O(1) running time when we use the known parameterized or approximation algorithms for finding a k-sized chordal deletion set on an n vertex graph. In this work, we design 2O(k)n O(1) time algorithms for these problems. Our algorithms do not compute a chordal vertex deletion set (or even an approximate solution). Instead, we construct a tree decomposition of the given graph in time 2O(k)n O(1) where each bag is a union of four cliques and O(k) vertices. We then apply standard dynamic programming algorithms over this special tree decomposition. This special tree decomposition can be of independent interest. Our algorithms are adaptive (robust) in the sense that given an integer k, they detect whether the graph has a chordal vertex deletion set of size at most k or output the special tree decomposition and solve the problem. This is analogous to the polynomial algorithm of Raghavan and Spinrad [J. of Algorithms, 2003] for finding a maximum clique in a unit disk graph without the unit disk representation. The algorithm either found a maximum clique in the graph or output a certificate that the given graph was not a unit disk graph, though it was known that determining whether a given graph was unit disk was NP-hard. We also show lower bounds for the problems we deal with under the Strong Exponential Time Hypothesis (SETH).
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