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Dieter Kratsch

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27 papers
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27

TCS Journal 2019 Journal Article

Enumeration and maximum number of minimal dominating sets for chordal graphs

  • Petr A. Golovach
  • Dieter Kratsch
  • Mathieu Liedloff
  • Mohamed Yosri Sayadi

We study the enumeration of the minimal dominating sets and upper bounds for the number of such sets in chordal graphs. We show that the maximum number of minimal dominating sets of an n-vertex chordal graph is at most 1. 5048 n and prove that these sets can be enumerated in time O ( 1. 5048 n ). In this way we improve the previous upper bound of 1. 5214 n, recently established by Abu-Khzam and Heggernes, and narrow the gap between the upper bound and the known lower bound of 1. 4422 n.

TCS Journal 2019 Journal Article

Enumeration of maximal irredundant sets for claw-free graphs

  • Petr A. Golovach
  • Dieter Kratsch
  • Mohamed Yosri Sayadi

Domination is one of the classical subjects in structural graph theory and in graph algorithms. The Minimum Dominating Set problem and many of its variants are NP-complete and have been studied from various algorithmic perspectives. One of those variants called irredundance is highly related to domination. For example, every minimal dominating set of a graph G is also a maximal irredundant set of G. In this paper we study the enumeration of the maximal irredundant sets of a claw-free graph. We show that an n-vertex claw-free graph has O ( 1. 9341 n ) maximal irredundant sets and these sets can be enumerated in the same time. We complement the aforementioned upper bound with a lower bound by providing a family of graphs having 1. 5848 n maximal irredundant sets.

TCS Journal 2017 Journal Article

A linear kernel for finding square roots of almost planar graphs

  • Petr A. Golovach
  • Dieter Kratsch
  • Daniël Paulusma
  • Anthony Stewart

A graph H is a square root of a graph G if G can be obtained from H by the addition of edges between any two vertices in H that are at distance 2 from each other. The Square Root problem is that of deciding whether a given graph admits a square root. We consider this problem for planar graphs in the context of the “distance from triviality” framework. For an integer k, a planar + k v graph (or k-apex graph) is a graph that can be made planar by the removal of at most k vertices. We prove that a generalization of Square Root, in which some edges are prescribed to be either in or out of any solution, has a kernel of size O ( k ) for planar + k v graphs, when parameterized by k. Our result is based on a new edge reduction rule which, as we shall also show, has a wider applicability for the Square Root problem.

TCS Journal 2017 Journal Article

Exact exponential algorithms to find tropical connected sets of minimum size

  • Mathieu Chapelle
  • Manfred Cochefert
  • Dieter Kratsch
  • Romain Letourneur
  • Mathieu Liedloff

Tropical Connected Set is strongly related to the Graph Motif problem which deals with vertex-colored graphs. Graph Motif has various applications in biology and metabolic networks, and has widely been studied in the last twenty years. The input of the Tropical Connected Set problem is a vertex-colored graph ( G, c ), where G = ( V, E ) is a graph and c is a vertex coloring assigning to each vertex of G a color. The task is to find a connected subset S ⊆ V of minimum size such that each color of G appears in S. This problem is known to be NP-complete, even when restricted to trees of height at most three. We study exact exponential algorithms to solve Tropical Connected Set. We present an O ⁎ ( 1. 5359 n ) time algorithm for general graphs and an O ⁎ ( 1. 2721 n ) time algorithm for trees. We also show that Tropical Connected Set on trees has no sub-exponential algorithm unless the Exponential Time Hypothesis fails.

TCS Journal 2016 Journal Article

Algorithms solving the Matching Cut problem

  • Dieter Kratsch
  • Van Bang Le

In a graph, a matching cut is an edge cut that is a matching. Matching Cut is the problem of deciding whether or not a given graph has a matching cut, which is known to be NP-complete. This paper provides a first branching algorithm solving Matching Cut in time O ⁎ ( 2 n / 2 ) = O ⁎ ( 1. 4143 n ) for an n-vertex input graph, and shows that Matching Cut parameterized by the vertex cover number τ ( G ) can be solved by a single-exponential algorithm in time 2 τ ( G ) O ( n 2 ). Moreover, the paper also gives a polynomially solvable case for Matching Cut which covers previous known results on graphs of maximum degree three, line graphs, and claw-free graphs.

TCS Journal 2016 Journal Article

Enumerating minimal connected dominating sets in graphs of bounded chordality

  • Petr A. Golovach
  • Pinar Heggernes
  • Dieter Kratsch

Enumerating objects of specified type is one of the principal tasks in algorithmics. In graph algorithms one often enumerates vertex subsets satisfying a certain property. We study the enumeration of all minimal connected dominating sets of an input graph from various graph classes of bounded chordality. We establish enumeration algorithms as well as lower and upper bounds for the maximum number of minimal connected dominating sets in such graphs. In particular, we present algorithms to enumerate all minimal connected dominating sets of chordal graphs in time O ( 1. 7159 n ), of split graphs in time O ( 1. 3803 n ), and of AT-free, strongly chordal, and distance-hereditary graphs in time O ⁎ ( 3 n / 3 ), where n is the number of vertices of the input graph. Our algorithms imply corresponding upper bounds for the number of minimal connected dominating sets for these graph classes.

MFCS Conference 2016 Conference Paper

Space-Efficient Biconnected Components and Recognition of Outerplanar Graphs

  • Frank Kammer
  • Dieter Kratsch
  • Moritz Laudahn

We present space-efficient algorithms for computing cut vertices in a given graph with n vertices and m edges in linear time using O(n+min{m, n log log n}) bits. With the same time and using O(n+m) bits, we can compute the biconnected components of a graph. We use this result to show an algorithm for the recognition of (maximal) outerplanar graphs in O(n log log n) time using O(n) bits.

TCS Journal 2015 Journal Article

Exact algorithms for Kayles

  • Hans L. Bodlaender
  • Dieter Kratsch
  • Sjoerd T. Timmer

In the game of Kayles, two players select alternatingly a vertex from a given graph G, but may never choose a vertex that is adjacent or equal to an already chosen vertex. The last player that can select a vertex wins the game. In this paper, we give an exact algorithm to determine which player has a winning strategy in this game. To analyze the running time of the algorithm, we introduce the notion of a K-set: a nonempty set of vertices W ⊆ V is a K-set in a graph G = ( V, E ), if G [ W ] is connected and there exists an independent set X such that W = V − N [ X ]. The running time of the algorithm is bounded by a polynomial factor times the number of K-sets in G. We prove that the number of K-sets in a graph with n vertices is bounded by O ( 1. 6052 n ). A computer-generated case analysis improves this bound to O ( 1. 6031 n ) K-sets, and thus we have an upper bound of O ( 1. 6031 n ) on the running time of the algorithm for Kayles. We also show that the number of K-sets in a tree is bounded by n ⋅ 3 n / 3 and thus Kayles can be solved on trees in O ( 1. 4423 n ) time. We show that apart from a polynomial factor, the number of K-sets in a tree is sharp. As corollaries, we obtain that determining which player has a winning strategy in the games G avoid ( POS DNF 2 ) and G seek ( POSDNF 3 ) can also be determined in O ( 1. 6031 n ) time. In G avoid ( POSDNF 2 ), we have a positive formula F on n Boolean variables in Disjunctive Normal Form with two variables per clause. Initially, all variables are false, and players alternately set a variable from false to true; the first player that makes F true loses the game. The game G seek ( POSDNF 3 ) is similar, but now there are three variables per clause, and the first player that makes F true wins the game.

TCS Journal 2013 Journal Article

Detecting induced minors in AT-free graphs

  • Petr A. Golovach
  • Dieter Kratsch
  • Daniël Paulusma

The Induced Minor problem is that of testing whether a graph G can be modified into a graph H by a sequence of vertex deletions and edge contractions. If only edge contractions are permitted, we obtain the Contractibility problem. We prove that Induced Minor is polynomial-time solvable when G is AT-free and H is fixed, i. e. , not part of the input. In addition, we show that Contractibility is polynomial-time solvable when G is AT-free and H is a fixed triangle-free graph. We complement these two results by proving that both problems are W[1]-hard on AT-free graphs when parameterized by | V H |.

I&C Journal 2013 Journal Article

Fixed-parameter algorithms for Cochromatic Number and Disjoint Rectangle Stabbing via iterative localization

  • Pinar Heggernes
  • Dieter Kratsch
  • Daniel Lokshtanov
  • Venkatesh Raman
  • Saket Saurabh

Given a permutation π of { 1, …, n } and a positive integer k, can π be partitioned into at most k subsequences, each of which is either increasing or decreasing? We give an algorithm with running time 2 O ( k 2 log k ) n O ( 1 ) that solves this problem, thereby showing that it is fixed parameter tractable. This NP-complete problem is equivalent to deciding whether the cochromatic number of a given permutation graph on n vertices is at most k. Our algorithm solves in fact a more general problem: within the mentioned running time, it decides whether the cochromatic number of a given perfect graph on n vertices is at most k. To obtain our result we use a combination of two well-known techniques within parameterized algorithms: iterative compression and greedy localization. Consequently we name this combination “iterative localization”. We further demonstrate the power of this combination by giving an algorithm with running time 2 O ( k 2 log k ) n log n that decides whether a given set of n non-overlapping axis-parallel rectangles can be stabbed by at most k of a given set of horizontal and vertical lines.

TCS Journal 2013 Journal Article

Minimal dominating sets in graph classes: Combinatorial bounds and enumeration

  • Jean-François Couturier
  • Pinar Heggernes
  • Pim van ’t Hof
  • Dieter Kratsch

The number of minimal dominating sets that a graph on n vertices can have is known to be at most 1. 715 9 n. This upper bound might not be tight, since no examples of graphs with 1. 570 5 n or more minimal dominating sets are known. For several classes of graphs, we substantially improve the upper bound on the number of minimal dominating sets. At the same time, we give algorithms for enumerating all minimal dominating sets, where the running time of each algorithm is within a polynomial factor of the proved upper bound for the graph class in question. In several cases, we provide examples of graphs containing the maximum possible number of minimal dominating sets for graphs in that class, thereby showing the corresponding upper bounds to be tight.

TCS Journal 2011 Journal Article

An exact algorithm for the Maximum Leaf Spanning Tree problem

  • Henning Fernau
  • Joachim Kneis
  • Dieter Kratsch
  • Alexander Langer
  • Mathieu Liedloff
  • Daniel Raible
  • Peter Rossmanith

Given an undirected graph with n vertices, the Maximum Leaf Spanning Tree problem is to find a spanning tree with as many leaves as possible. When parameterized in the number of leaves k, this problem can be solved in time O ( 4 k poly ( n ) ) using a simple branching algorithm introduced by a subset of the authors (Kneis et al. 2008 [16]). Daligault et al. (2010) [6] improved the branching and obtained a running time of O ( 3. 7 2 k poly ( n ) ). In this paper, we study the problem from an exponential time viewpoint, where it is equivalent to the Connected Dominating Set problem. Here, Fomin, Grandoni, and Kratsch showed how to break the Ω ( 2 n ) barrier and proposed an O ( 1. 940 7 n ) -time algorithm (Fomin et al. 2008 [11]). Based on some useful properties of Kneis et al. (2008) [16] and Daligault et al. (2010) [6], we present a branching algorithm whose running time of O ( 1. 896 6 n ) has been analyzed using the Measure-and-Conquer technique. Finally, we provide a lower bound of Ω ( 1. 442 2 n ) for the worst case running time of our algorithm.

TCS Journal 2011 Journal Article

Bandwidth on AT-free graphs

  • Petr Golovach
  • Pinar Heggernes
  • Dieter Kratsch
  • Daniel Lokshtanov
  • Daniel Meister
  • Saket Saurabh

We study the classical Bandwidth problem from the viewpoint of parametrised algorithms. Given a graph G = ( V, E ) and a positive integer k, the Bandwidth problem asks whether there exists a bijective function β: { 1, …, ∣ V ∣ } → V such that for every edge u v ∈ E, ∣ β − 1 ( u ) − β − 1 ( v ) ∣ ≤ k. It is known that under standard complexity assumptions, no algorithm for Bandwidth with running time of the form f ( k ) n O ( 1 ) exists, even when the input is restricted to trees. We initiate the search for classes of graphs where such algorithms do exist. We present an algorithm with running time n ⋅ 2 O ( k log k ) for Bandwidth on AT-free graphs, a well-studied graph class that contains interval, permutation, and cocomparability graphs. Our result is the first non-trivial algorithm that shows fixed-parameter tractability of Bandwidth on a graph class on which the problem remains NP -complete.

TCS Journal 2010 Journal Article

Iterative compression and exact algorithms

  • Fedor V. Fomin
  • Serge Gaspers
  • Dieter Kratsch
  • Mathieu Liedloff
  • Saket Saurabh

Iterative compression has recently led to a number of breakthroughs in parameterized complexity. Here, we show that the technique can also be useful in the design of exact exponential time algorithms to solve NP-hard problems. We exemplify our findings with algorithms for the Maximum Independent Set problem, a parameterized and a counting version of d -Hitting Set and the Maximum Induced Cluster Subgraph problem.

MFCS Conference 2008 Conference Paper

Iterative Compression and Exact Algorithms

  • Fedor V. Fomin
  • Serge Gaspers
  • Dieter Kratsch
  • Mathieu Liedloff
  • Saket Saurabh 0001

Abstract Iterative Compression has recently led to a number of breakthroughs in parameterized complexity. The main purpose of this paper is to show that iterative compression can also be used in the design of exact exponential time algorithms. We exemplify our findings with algorithms for the Maximum Independent Set problem, a counting version of k - Hitting Set and the Maximum Induced Cluster Subgraph problem.

TCS Journal 2007 Journal Article

An exact algorithm for the minimum dominating clique problem

  • Dieter Kratsch
  • Mathieu Liedloff

A subset of vertices D ⊆ V of a graph G = ( V, E ) is a dominating clique if D is a dominating set and a clique of G. The existence problem ‘Given a graph G, is there a dominating clique in G? ’ is NP-complete, and thus both the Minimum and the Maximum Dominating Clique problems are NP-hard. We present an O ( 1. 338 7 n ) time and polynomial space algorithm that for an input graph on n vertices either computes a minimum dominating clique or reports that the graph has no dominating clique. The algorithm uses the Branch & Reduce paradigm and its time analysis is based on the Measure & Conquer approach. We also establish a lower bound of Ω ( 1. 259 9 n ) for the worst case running time of the algorithm. Finally using memorization we obtain an O ( 1. 323 4 n ) time and exponential space algorithm for the same problem.

MFCS Conference 2007 Conference Paper

Exact Algorithms for L (2, 1)-Labeling of Graphs

  • Jan Kratochvíl
  • Dieter Kratsch
  • Mathieu Liedloff

Abstract The notion of distance constrained graph labelings, motivated by the Frequency Assignment Problem, reads as follows: A mapping from the vertex set of a graph G = ( V, E ) into an interval of integers [0. . k ] is an L (2, 1)-labeling of G of span k if any two adjacent vertices are mapped onto integers that are at least 2 apart, and every two vertices with a common neighbor are mapped onto distinct integers. It is known that for any fixed k ≥ 4, deciding the existence of such a labeling is an NP-complete problem. We present exact exponential time algorithms that are faster than the naive O (( k + 1) n ) algorithm that would try all possible mappings. The improvement is best seen in the first NP-complete case of k = 4 – here the running time of our algorithm is O (1. 3161 n ).

MFCS Conference 2006 Conference Paper

Optimal Linear Arrangement of Interval Graphs

  • Johanne Cohen
  • Fedor V. Fomin
  • Pinar Heggernes
  • Dieter Kratsch
  • Gregory Kucherov

Abstract We study the optimal linear arrangement (OLA) problem on interval graphs. Several linear layout problems that are NP-hard on general graphs are solvable in polynomial time on interval graphs. We prove that, quite surprisingly, optimal linear arrangement of interval graphs is NP-hard. The same result holds for permutation graphs. We present a lower bound and a simple and fast 2-approximation algorithm based on any interval model of the input graph.

TCS Journal 2005 Journal Article

On algorithms for ( P 5,gem)-free graphs

  • Hans L. Bodlaender
  • Andreas Brandstädt
  • Dieter Kratsch
  • Michaël Rao
  • Jeremy Spinrad

A graph is ( P 5, gem)-free, when it does not contain P 5 (an induced path with five vertices) or a gem (a graph formed by making an universal vertex adjacent to each of the four vertices of the induced path P 4 ) as an induced subgraph. We present O ( n 2 ) time recognition algorithms for chordal gem-free graphs and for ( P 5, gem)-free graphs. Using a characterization of ( P 5, gem)-free graphs by their prime graphs with respect to modular decomposition and their modular decomposition trees [A. Brandstädt, D. Kratsch, On the structure of ( P 5, gem)-free graphs, Discrete Appl. Math. 145 (2005), 155–166], we give linear time algorithms for the following NP-complete problems on ( P 5, gem)-free graphs: Minimum Coloring; Maximum Weight Stable Set; Maximum Weight Clique; and Minimum Clique Cover.

MFCS Conference 1998 Conference Paper

Degree-Preserving Forests

  • Hajo Broersma
  • Andreas Huck
  • Ton Kloks
  • Otto R. Koppius
  • Dieter Kratsch
  • Haiko Müller
  • Hilde Tuinstra

Abstract We consider the degree-preserving spanning tree (DPST) problem: given a connected graph G, find a spanning tree T of G such that as many vertices of T as possible have the same degree in T as in G. This problem is a graph-theoretical translation of a problem arising in the system-theoretical context of identifiability in networks, a concept which has applications in e. g. , water distribution networks and electrical networks. We show that the DPST problem is NP-complete, even when restricted to split graphs or bipartite planar graphs. We present linear time approximation algorithms for planar graphs of worst case performance ratio 1−ε for every constant ε > 0. Furthermore we give exact algorithms for interval graphs (linear time), graphs of bounded treewidth (linear time), cocomparability graphs (O(n 4 )), and graphs of bounded asteroidal number.

TCS Journal 1997 Journal Article

On treewidth and minimum fill-in of asteroidal triple-free graphs

  • Ton Kloks
  • Dieter Kratsch
  • Jeremy Spinrad

We present O(n 5 R + n 3 R 3) time algorithms to compute the treewidth, pathwidth, minimum fill-in and minimum interval graph completion of asteroidal triple-free graphs, where n is the number of vertices and R is the number of minimal separators of the input graph. This yields polynomial time algorithms for the four NP-complete graph problems on any subclass of the asteroidal triple-free graphs that has a polynomially bounded number of minimal separators, as e. g. cocomparability graphs of bounded dimension and d-trapezoid graphs for any fixed d ⩾ 1.

TCS Journal 1992 Journal Article

The complexity of coloring games on perfect graphs

  • Hans L. Bodlaender
  • Dieter Kratsch

In this paper we consider the following type of game: two players must color the vertices of a given graph G = (V, E), in a prescribed order, in such a way that no two adjacent vertices are colored with the same color. In one variant, the first player which is unable to move loses the game. In another variant, player 1 wins the game, if and only if the game ends with all vertices colored. In this paper, we obtain several results on the complexity of the problem to decide whether there is a winning strategy for player 1 in a given game instance, when G is restricted to split graphs, interval graphs, or bipartite graphs.

I&C Journal 1987 Journal Article

Finding the minimum bandwidth of an interval graph

  • Dieter Kratsch

An assignment of unique integers to the vertices of a graph is called a linear layout. The bandwidth minimization problem (BANDWIDTH) is the following: Given a graph G = (V, E) and an integer k, determine whether there exists a linear layout of G such that the maximum difference between adjacent vertices is bounded by k. Interval graphs are the intersection graphs of a family of intervals of the real line. BANDWIDTH remains NP-complete even when restricted to special subclasses of trees. We show that BANDWIDTH can be solved in time O(n 2) for interval graphs. Moreover, for a given interval graph a linear layout with minimum bandwidth can be constructed in time O(n 2logn). As a by-product we get that this construction can be done for proper interval graphs in time O(nlog n+m).

TCS Journal 1987 Journal Article

On domination problems for permutation and other graphs

  • Andreas Brandstädt
  • Dieter Kratsch

There is an increasing interest in results on the influence of restricting NP-complete graph problems to special classes of perfect graphs as, e. g. , permutation graphs. It was shown that several problems restricted to permutation graphs are solvable in polynomial time [2, 3, 4, 6, 7, 14, 16]. In this paper we give 1. (i) an algorithm with time bound O(n 2) for the weighted independent domination problem on permutation graphs (which is an improvement of the O(n 3) solution given in [7]); 2. (ii) a polynomial time solution for the weighted feedback vertex set problem on permutation graphs; 3. (iii) an investigation of (weighted) dominating clique problems for several graph classes including an NP-completeness result for weakly triangulated graphs as well as polynomial time bounds.

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