Emergent Mind

Parameterized (Approximate) Defective Coloring

(1801.03879)
Published Jan 11, 2018 in cs.DS and cs.CC

Abstract

In Defective Coloring we are given a graph $G = (V, E)$ and two integers $\chid, \Delta*$ and are asked if we can partition $V$ into $\chid$ color classes, so that each class induces a graph of maximum degree $\Delta*$. We investigate the complexity of this generalization of Coloring with respect to several well-studied graph parameters, and show that the problem is W-hard parameterized by treewidth, pathwidth, tree-depth, or feedback vertex set, if $\chid = 2$. As expected, this hardness can be extended to larger values of $\chid$ for most of these parameters, with one surprising exception: we show that the problem is FPT parameterized by feedback vertex set for any $\chid \ge 2$, and hence 2-coloring is the only hard case for this parameter. In addition to the above, we give an ETH-based lower bound for treewidth and pathwidth, showing that no algorithm can solve the problem in $n{o(pw)}$, essentially matching the complexity of an algorithm obtained with standard techniques. We complement these results by considering the problem's approximability and show that, with respect to $\Delta*$, the problem admits an algorithm which for any $\epsilon > 0$ runs in time $(tw/\epsilon){O(tw)}$ and returns a solution with exactly the desired number of colors that approximates the optimal $\Delta*$ within $(1 + \epsilon)$. We also give a $(tw){O(tw)}$ algorithm which achieves the desired $\Delta*$ exactly while 2-approximating the minimum value of $\chid$. We show that this is close to optimal, by establishing that no FPT algorithm can (under standard assumptions) achieve a better than $3/2$-approximation to $\chi_d$, even when an extra constant additive error is also allowed.

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