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Register a new userAn Improved Deterministic Parameterized Algorithm for Cactus Vertex Deletion
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Yasuaki Kobayashi
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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A cactus is a connected graph that does not contain $K_4 - e$ as a minor. Given a graph $G = (V, E)$ and integer $k ge 0$, Cactus Vertex Deletion (also known as Diamond Hitting Set) is the problem of deciding whether $G$ has a vertex set of size at most $k$ whose removal leaves a forest of cacti. The current best deterministic parameterized algorithm for this problem was due to Bonnet et al. [WG 2016], which runs in time $26^kn^{O(1)}$, where $n$ is the number of vertices of $G$. In this paper, we design a deterministic algorithm for Cactus Vertex Deletion, which runs in time $17.64^kn^{O(1)}$. As a straightforward application of our algorithm, we give a $17.64^kn^{O(1)}$-time algorithm for Even Cycle Transversal. The idea behind this improvement is to apply the measure and conquer analysis with a slightly elaborate measure of instances.
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In the Directed Feedback Vertex Set (DFVS) problem, the input is a directed graph $D$ on $n$ vertices and $m$ edges, and an integer $k$. The objective is to determine whether there exists a set of at most $k$ vertices intersecting every directed cycle of $D$. Whether or not DFVS admits a fixed parameter tractable (FPT) algorithm was considered the most important open problem in parameterized complexity until Chen, Liu, Lu, OSullivan and Razgon [JACM 2008] answered the question in the affirmative. They gave an algorithm for the problem with running time $O(k!4^kk^4nm)$. Since then, no faster algorithm for the problem has been found. In this paper, we give an algorithm for DFVS with running time $O(k!4^kk^5(n+m))$. Our algorithm is the first algorithm for DFVS with linear dependence on input size. Furthermore, the asymptotic dependence of the running time of our algorithm on the parameter $k$ matches up to a factor $k$ the algorithm of Chen, Liu, Lu, OSullivan and Razgon. On the way to designing our algorithm for DFVS, we give a general methodology to shave off a factor of $n$ from iterative-compression based algorithms for a few other well-studied covering problems in parameterized complexity. We demonstrate the applicability of this technique by speeding up by a factor of $n$, the current best FPT algorithms for Multicut [STOC 2011, SICOMP 2014] and Directed Subset Feedback Vertex Set [ICALP 2012, TALG 2014].
The pathwidth of a graph is a measure of how path-like the graph is. Given a graph G and an integer k, the problem of finding whether there exist at most k vertices in G whose deletion results in a graph of pathwidth at most one is NP- complete. We initiate the study of the parameterized complexity of this problem, parameterized by k. We show that the problem has a quartic vertex-kernel: We show that, given an input instance (G = (V, E), k); |V| = n, we can construct, in polynomial time, an instance (G, k) such that (i) (G, k) is a YES instance if and only if (G, k) is a YES instance, (ii) G has O(k^{4}) vertices, and (iii) k leq k. We also give a fixed parameter tractable (FPT) algorithm for the problem that runs in O(7^{k} k cdot n^{2}) time.
In the Disjoint Paths problem, the input is an undirected graph $G$ on $n$ vertices and a set of $k$ vertex pairs, ${s_i,t_i}_{i=1}^k$, and the task is to find $k$ pairwise vertex-disjoint paths connecting $s_i$ to $t_i$. The problem was shown to have an $f(k)n^3$ algorithm by Robertson and Seymour. In modern terminology, this means that Disjoint Paths is fixed parameter tractable (FPT), parameterized by the number of vertex pairs. This algorithm is the cornerstone of the entire graph minor theory, and a vital ingredient in the $g(k)n^3$ algorithm for Minor Testing (given two undirected graphs, $G$ and $H$ on $n$ and $k$ vertices, respectively, the objective is to check whether $G$ contains $H$ as a minor). All we know about $f$ and $g$ is that these are computable functions. Thus, a challenging open problem in graph algorithms is to devise an algorithm for Disjoint Paths where $f$ is single exponential. That is, $f$ is of the form $2^{{sf poly}(k)}$. The algorithm of Robertson and Seymour relies on topology and essentially reduces the problem to surface-embedded graphs. Thus, the first major obstacle that has to be overcome in order to get an algorithm with a single exponential running time for Disjoint Paths and {sf Minor Testing} on general graphs is to solve Disjoint Paths in single exponential time on surface-embedded graphs and in particular on planar graphs. Even when the inputs to Disjoint Paths are restricted to planar graphs, a case called the Planar Disjoint Paths problem, the best known algorithm has running time $2^{2^{O(k)}}n^2$. In this paper, we make the first step towards our quest for designing a single exponential time algorithm for Disjoint Paths by giving a $2^{O(k^2)}n^{O(1)}$-time algorithm for Planar Disjoint Paths.
Graph-modification problems, where we add/delete a small number of vertices/edges to make the given graph to belong to a simpler graph class, is a well-studied optimization problem in all algorithmic paradigms including classical, approximation and parameterized complexity. Specifically, graph-deletion problems, where one needs to delete at most $k$ vertices to place it in a given non-trivial hereditary (closed under induced subgraphs) graph class, captures several well-studied problems including {sc Vertex Cover}, {sc Feedback Vertex Set}, {sc Odd Cycle Transveral}, {sc Cluster Vertex Deletion}, and {sc Perfect Deletion}. Investigation into these problems in parameterized complexity has given rise to powerful tools and techniques. While a precise characterization of the graph classes for which the problem is {it fixed-parameter tractable} (FPT) is elusive, it has long been known that if the graph class is characterized by a {it finite} set of forbidden graphs, then the problem is FPT. In this paper, we initiate a study of a natural variation of the problem of deletion to {it scattered graph classes} where we need to delete at most $k$ vertices so that in the resulting graph, each connected component belongs to one of a constant number of graph classes. A simple hitting set based approach is no longer feasible even if each of the graph classes is characterized by finite forbidden sets. As our main result, we show that this problem is fixed-parameter tractable (FPT) when the deletion problem corresponding to each of the finite classes is known to be FPT and the properties that a graph belongs to each of the classes is expressible in CMSO logic. When each graph class has a finite forbidden set, we give a faster FPT algorithm using the well-known techniques of iterative compression and important separators.
A graph is $d$-orientable if its edges can be oriented so that the maximum in-degree of the resulting digraph is at most $d$. $d$-orientability is a well-studied concept with close connections to fundamental graph-theoretic notions and applications as a load balancing problem. In this paper we consider the d-ORIENTABLE DELETION problem: given a graph $G=(V,E)$, delete the minimum number of vertices to make $G$ $d$-orientable. We contribute a number of results that improve the state of the art on this problem. Specifically: - We show that the problem is W[2]-hard and $log n$-inapproximable with respect to $k$, the number of deleted vertices. This closes the gap in the problems approximability. - We completely characterize the parameterized complexity of the problem on chordal graphs: it is FPT parameterized by $d+k$, but W-hard for each of the parameters $d,k$ separately. - We show that, under the SETH, for all $d,epsilon$, the problem does not admit a $(d+2-epsilon)^{tw}$, algorithm where $tw$ is the graphs treewidth, resolving as a special case an open problem on the complexity of PSEUDOFOREST DELETION. - We show that the problem is W-hard parameterized by the input graphs clique-width. Complementing this, we provide an algorithm running in time $d^{O(dcdot cw)}$, showing that the problem is FPT by $d+cw$, and improving the previously best known algorithm for this case.
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