arXiv subjects
Publications and source records attributed to Ekkehard Köhler.
A clique transversal of a graph is a set of vertices intersecting every maximal clique. We prove that deciding whether a graph has an inclusion-wise minimal clique transversal of size at least $k$ is W[1]-hard when parameterized by $k$.
We study a variation of the classical Maximum (Minimum) Leaf Spanning Tree problem. In many applications, Depth-First Search (DFS) is used to compute a spanning tree of a graph. Such a search tree is constructed by connecting each vertex $v$ with the last vertex the search has visited before $v$ and we call this a last-in tree. By restricting the Maximum (Minimum) Leaf Spanning Tree problem to last-in trees of a graph search, we ask for a search ordering that leads to the largest (smallest) number of leaves in its search tree. Recently, Bergougnoux et al. [Journal of Computer and System Sciences 154 (2025)] have studied the parameterized complexity of these problems for DFS. They showed that the minimization problem is para-$\mathsf{NP}$-hard and the maximization problem is $\mathsf{W}[1]$-hard when parameterized by the number of leaves. When parameterized by the number of internal vertices, both problems have polynomial kernels. Here, we examine whether these results also hold for the variant Lexicographic DFS (LDFS). We show that the hardness results of DFS can be transferred to LDFS. We also present exponential kernels for the number of internal vertices as the parameter. We complement this by showing that polynomial kernels do not exist, unless $\mathsf{NP} \subseteq \mathsf{coNP} / \mathsf{poly}$. We also consider last-in trees of searches that do not follow the DFS scheme. In contrast to (L)DFS, minimizing the number of internal vertices is para-$\mathsf{NP}$-hard for several searches including Breadth-First Search.
Edge-weighted graphs play an important role in the theory of Robinsonian matrices and similarity theory, particularly via the concept of level graphs, that is, graphs obtained from an edge-weighted graph by removing all sufficiently light edges. This suggests a natural way of associating to any class $\mathcal{G}$ of unweighted graphs a corresponding class of edge-weighted graphs, namely by requiring that all level graphs belong to $\mathcal{G}$. We show that for weighted graphs $G=(V,E)$ with weights from $\{1,\dots,|E|\}$ we can decide in linear time whether all level graphs are split, threshold, or chain graphs using special edge elimination orderings. We obtain these results by introducing the notion of degree sandwich monotone graph classes. A graph class $\mathcal{G}$ is sandwich monotone if every edge set which may be removed from a graph in $\mathcal{G}$ without leaving the class also contains a single edge that can be safely removed. Furthermore, if we require the safe edge to fulfill a certain degree property, then $\mathcal{G}$ is called degree sandwich monotone. We present necessary and sufficient conditions for the existence of a linear-time recognition algorithm for any weighted graph class whose corresponding unweighted class is degree sandwich monotone and contains all edgeless graphs.
The Maximum (Minimum) Leaf Spanning Tree problem asks for a spanning tree with the largest (smallest) number of leaves. As spanning trees are often computed using graph search algorithms, it is natural to restrict this problem to the set of search trees of some particular graph search, e.g., find the Breadth-First Search (BFS) tree with the largest number of leaves. We study this problem for Generic Search (GS), BFS and Lexicographic Breadth-First Search (LBFS) using search trees that connect each vertex to its first neighbor in the search order (first-in trees) just like the classic BFS tree. In particular, we analyze the complexity of these problems, both in the classical and in the parameterized sense. Among other results, we show that the minimum and maximum leaf problems are in FPT for the first-in trees of GS, BFS and LBFS when parameterized by the number of leaves in the tree. However, when these problems are parameterized by the number of internal vertices of the tree, they are W[1]-hard for the first-in trees of GS, BFS and LBFS.
In this paper we present various lower bound results on collective tree spanners and on spanners of bounded treewidth. A graph $G$ is said to admit a system of $μ$ collective additive tree $c$-spanners if there is a system $\cal{T}$$(G)$ of at most $μ$ spanning trees of $G$ such that for any two vertices $u,v$ of $G$ a tree $T\in \cal{T}$$(G)$ exists such that the distance in $T$ between $u$ and $v$ is at most $c$ plus their distance in $G$. A graph $G$ is said to admit an additive $k$-treewidth $c$-spanner if there is a spanning subgraph $H$ of $G$ with treewidth $k$ such that for any pair of vertices $u$ and $v$ their distance in $H$ is at most $c$ plus their distance in $G$. Among other results, we show that: $\bullet$ Any system of collective additive tree $1$ -- spanners must have $Ω(\sqrt[3]{\log n})$ spanning trees for some unit interval graphs; $\bullet$ No system of a constant number of collective additive tree $2$-spanners can exist for strongly chordal graphs; $\bullet$ No system of a constant number of collective additive tree $3$-spanners can exist for chordal graphs; $\bullet$ No system of a constant number of collective additive tree $c$-spanners can exist for weakly chordal graphs as well as for outerplanar graphs for any constant $c\geq 0$; $\bullet$ For any constants $k \ge 2$ and $c \ge 1$ there are graphs of treewidth $k$ such that no spanning subgraph of treewidth $k-1$ can be an additive $c$-spanner of such a graph. All these lower bound results apply also to general graphs. Furthermore, they %results complement known upper bound results with tight lower bound results.
Two graph parameters are said to be coarsely equivalent if they are within constant factors from each other for every graph $G$. Recently, several graph parameters were shown to be coarsely equivalent to tree-length. Recall that the length of a tree-decomposition ${\cal T}(G)$ of a graph $G$ is the largest diameter of a bag in ${\cal T}(G)$, and the tree-length $tl(G)$ of $G$ is the minimum of the length, over all tree-decompositions of $G$. Similarly, the length of a path-decomposition ${\cal P}(G)$ of a graph $G$ is the largest diameter of a bag in ${\cal P}(G)$, and the path-length $pl(G)$ of $G$ is the minimum of the length, over all path-decompositions of $G$. In this paper, we present several graph parameters that are coarsely equivalent to path-length. Among other results, we show that the path-length of a graph $G$ is small if and only if one of the following equivalent conditions is true: (a) $G$ can be embedded to an unweighted caterpillar tree (equivalently, to a graph of path-width one) with a small additive distortion; (b) there is a constant $r\ge 0$ such that for every triple of vertices $u,v,w$ of $G$, disk of radius $r$ centered at one of them intercepts all paths connecting two others; (c) $G$ has a $k$-dominating shortest path with small $k\ge 0$; (d) $G$ has a $k'$-dominating pair with small $k'\ge 0$; (e) some power $G^μ$ of $G$ is an AT-free (or even a cocomparability) graph for a small integer $μ\ge 0$.
The last in-tree recognition problem asks whether a given spanning tree can be derived by connecting each vertex with its rightmost left neighbor of some search ordering. In this study, we demonstrate that the last-in-tree recognition problem for Generic Search is $\mathsf{NP}$-complete. We utilize this finding to strengthen a complexity result from order theory. Given a partial order $π$ and a set of triples, the $\mathsf{NP}$-complete intermezzo problem asks for a linear extension of $π$ where each first element of a triple is not between the other two. We show that this problem remains $\mathsf{NP}$-complete even when the Hasse diagram of the partial order forms a tree of bounded height. In contrast, we give an $\mathsf{XP}$-algorithm for the problem when parameterized by the width of the partial order. Furthermore, we show that $\unicode{x2013}$ under the assumption of the Exponential Time Hypothesis $\unicode{x2013}$ the running time of this algorithm is asymptotically optimal.
We propose a novel way of generalizing the class of interval graphs, via a graph width parameter called the simultaneous interval number. This parameter is related to the simultaneous representation problem for interval graphs and defined as the smallest number $d$ of labels such that the graph admits a $d$-simultaneous interval representation, that is, an assignment of intervals and label sets to the vertices such that two vertices are adjacent if and only if the corresponding intervals, as well as their label sets, intersect. We show that this parameter is $\mathsf{NP}$-hard to compute and give several bounds for the parameter, showing in particular that it is sandwiched between pathwidth and linear mim-width. For classes of graphs with bounded parameter values, assuming that the graph is equipped with a simultaneous interval representation with a constant number of labels, we give $\mathsf{FPT}$ algorithms for the clique, independent set, and dominating set problems, and hardness results for the independent dominating set and coloring problems. The $\mathsf{FPT}$ results for independent set and dominating set are for the simultaneous interval number plus solution size. In contrast, both problems are known to be $\mathsf{W}[1]$-hard for linear mim-width plus solution size.
Lexicographic Depth First Search (LexDFS) is a special variant of a Depth First Search (DFS), which was introduced by Corneil and Krueger in 2008. While this search has been used in various applications, in contrast to other graph searches, no general linear time implementation is known to date. In 2014, Köhler and Mouatadid achieved linear running time to compute some special LexDFS orders for cocomparability graphs. In this paper, we present a linear time implementation of LexDFS for chordal graphs. Our algorithm is able to find any LexDFS order for this graph class. To the best of our knowledge this is the first unrestricted linear time implementation of LexDFS on a non-trivial graph class. In the algorithm we use a search tree computed by Lexicographic Breadth First Search (LexBFS).
End vertices of graph searches can exhibit strong structural properties and are crucial for many graph algorithms. The problem of deciding whether a given vertex of a graph is an end-vertex of a particular search was first introduced by Corneil, Köhler and Lanlignel in 2010. There they showed that this problem is in fact NP-complete for LBFS on weakly chordal graphs. A similar result for BFS was obtained by Charbit, Habib and Mamcarz in 2014. Here, we prove that the end-vertex problem is NP-complete for MNS on weakly chordal graphs and for MCS on general graphs. Moreover, building on previous results, we show that this problem is linear for various searches on split and unit interval graphs.
Graph searches and the corresponding search trees can exhibit important structural properties and are used in various graph algorithms. The problem of deciding whether a given spanning tree of a graph is a search tree of a particular search on this graph was introduced by Hagerup and Nowak in 1985, and independently by Korach and Ostfeld in 1989 where the authors showed that this problem is efficiently solvable for DFS trees. A linear time algorithm for BFS trees was obtained by Manber in 1990. In this paper we prove that the search tree problem is also in P for LDFS, in contrast to LBFS, MCS, and MNS, where we show NP-completeness. We complement our results by providing linear time algorithms for these searches on split graphs.
In this paper, we present a cyclically time-expanded network model for simultaneous optimization of traffic assignment and traffic signal parameters, in particular offsets, split times, and phase orders. Since travel times are of great importance for developing realistic solutions for traffic assignment and traffic signal coordination in urban road networks, we perform an extensive analysis of the model. We show that a linear time-expanded model can reproduce realistic travel times especially for use with traffic signals and we verify this by simulation. Furthermore, we show how exact mathematical programming techniques can be used for optimizing the control of traffic signals. We provide computational results for real world instances and demonstrate the capabilities of the cyclically time-expanded by simulation results obtained with state-of-the-art traffic simulation tools.
We investigate the minimum line-distortion and the minimum bandwidth problems on unweighted graphs and their relations with the minimum length of a Robertson-Seymour's path-decomposition. The length of a path-decomposition of a graph is the largest diameter of a bag in the decomposition. The path-length of a graph is the minimum length over all its path-decompositions. In particular, we show: - if a graph $G$ can be embedded into the line with distortion $k$, then $G$ admits a Robertson-Seymour's path-decomposition with bags of diameter at most $k$ in $G$; - for every class of graphs with path-length bounded by a constant, there exist an efficient constant-factor approximation algorithm for the minimum line-distortion problem and an efficient constant-factor approximation algorithm for the minimum bandwidth problem; - there is an efficient 2-approximation algorithm for computing the path-length of an arbitrary graph; - AT-free graphs and some intersection families of graphs have path-length at most 2; - for AT-free graphs, there exist a linear time 8-approximation algorithm for the minimum line-distortion problem and a linear time 4-approximation algorithm for the minimum bandwidth problem.
Lexicographic depth first search (LexDFS) is a graph search protocol which has already proved to be a powerful tool on cocomparability graphs. Cocomparability graphs have been well studied by investigating their complements (comparability graphs) and their corresponding posets. Recently however LexDFS has led to a number of elegant polynomial and near linear time algorithms on cocomparability graphs when used as a preprocessing step [2, 3, 11]. The nonlinear runtime of some of these results is a consequence of complexity of this preprocessing step. We present the first linear time algorithm to compute a LexDFS cocomparability ordering, therefore answering a problem raised in [2] and helping achieve the first linear time algorithms for the minimum path cover problem, and thus the Hamilton path problem, the maximum independent set problem and the minimum clique cover for this graph family.