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Johannes Zink

Publications and source records attributed to Johannes Zink.

32 records · Page 2Linked to original sources

Coloring and Recognizing Directed Interval Graphs

A \emph{mixed interval graph} is an interval graph that has, for every pair of intersecting intervals, either an arc (directed arbitrarily) or an (undirected) edge. We are particularly interested in scenarios where edges and arcs are defined by the geometry of intervals. In a proper coloring of a mixed interval graph $G$, an interval $u$ receives a lower (different) color than an interval $v$ if $G$ contains arc $(u,v)$ (edge $\{u,v\}$). Coloring of mixed graphs has applications, for example, in scheduling with precedence constraints; see a survey by Sotskov [Mathematics, 2020]. For coloring general mixed interval graphs, we present a $\min \{ω(G), λ(G)+1 \}$-approximation algorithm, where $ω(G)$ is the size of a largest clique and $λ(G)$ is the length of a longest directed path in $G$. For the subclass of \emph{bidirectional interval graphs} (introduced recently for an application in graph drawing), we show that optimal coloring is NP-hard. This was known for general mixed interval graphs. We introduce a new natural class of mixed interval graphs, which we call \emph{containment interval graphs}. In such a graph, there is an arc $(u,v)$ if interval $u$ contains interval $v$, and there is an edge $\{u,v\}$ if $u$ and $v$ overlap. We show that these graphs can be recognized in polynomial time, that coloring them with the minimum number of colors is NP-hard, and that there is a 2-approximation algorithm for coloring.

cs.DM↗

Tree Drawings with Columns

Our goal is to visualize an additional data dimension of a tree with multifaceted data through superimposition on vertical strips, which we call columns. Specifically, we extend upward drawings of unordered rooted trees where vertices have assigned heights by mapping each vertex to a column. Under an orthogonal drawing style and with every subtree within a column drawn planar, we consider different natural variants concerning the arrangement of subtrees within a column. We show that minimizing the number of crossings in such a drawing can be achieved in fixed-parameter tractable (FPT) time in the maximum vertex degree $Δ$ for the most restrictive variant, while becoming NP-hard (even to approximate) already for a slightly relaxed variant. However, we provide an FPT algorithm in the number of crossings plus $Δ$, and an FPT-approximation algorithm in $Δ$ via a reduction to feedback arc set.

cs.CG↗

Layered Drawing of Undirected Graphs with Generalized Port Constraints

The aim of this research is a practical method to draw cable plans of complex machines. Such plans consist of electronic components and cables connecting specific ports of the components. Since the machines are configured for each client individually, cable plans need to be drawn automatically. The drawings must be well readable so that technicians can use them to debug the machines. In order to model plug sockets, we introduce port groups; within a group, ports can change their position (which we use to improve the aesthetics of the layout), but together the ports of a group must form a contiguous block. We approach the problem of drawing such cable plans by extending the well-known Sugiyama framework such that it incorporates ports and port groups. Since the framework assumes directed graphs, we propose several ways to orient the edges of the given undirected graph. We compare these methods experimentally, both on real-world data and synthetic data that carefully simulates real-world data. We measure the aesthetics of the resulting drawings by counting bends and crossings. Using these metrics, we experimentally compare our approach to Kieler [JVLC 2014], a library for drawing graphs in the presence of port constraints. Our method produced 10--30 % fewer crossings, while it performed equally well or slightly worse than Kieler with respect to the number of bends and the time used to compute a drawing.

cs.DS↗

Polyline Simplification under the Local Fréchet Distance has Almost-Quadratic Runtime in 2D

Given a polyline on $n$ vertices, the polyline simplification problem asks for a minimum size subsequence of these vertices defining a new polyline whose distance to the original polyline is at most a given threshold under some distance measure, usually the local Hausdorff or the local Fréchet distance. Here, local means that, for each line segment of the simplified polyline, only the distance to the corresponding sub-curve in the original polyline is measured. Melkman and O'Rourke [Computational Morphology '88] introduced a geometric data structure to solve polyline simplification under the local Hausdorff distance in $O(n^2 \log n)$ time, and Guibas, Hershberger, Mitchell, and Snoeyink [Int. J. Comput. Geom. Appl. '93] considered polyline simplification under the Fréchet distance as ordered stabbing and provided an algorithm with a running time of $O(n^2 \log^2 n)$, but they did not restrict the simplified polyline to use only vertices of the original polyline. We show that their techniques can be adjusted to solve polyline simplification under the local Fréchet distance in $O(n^2 \log n)$ time instead of $O(n^3)$ when applying the Imai--Iri algorithm. Our algorithm may serve as a more efficient subroutine for multiple other algorithms. We provide a simple algorithm description as well as rigorous proofs to substantiate this theorem. We also investigate the geometric data structure introduced by Melkman and O'Rourke, which we refer to as wavefront, in more detail and feature some interesting properties. As a result, we can prove that under the L$_1$ and the L$_\infty$ norm, the algorithm can be significantly simplified and then only requires a running time of $O(n^2)$. We also define a natural class of polylines where our algorithm always achieves this running time also in the Euclidean norm L$_2$.

cs.CG↗

Upward Planar Drawings with Three and More Slopes

The slope number of a graph $G$ is the smallest number of slopes needed for the segments representing the edges in any straight-line drawing of $G$. It serves as a measure of the visual complexity of a graph drawing. Several bounds on the slope number for particular graph classes have been established, both in the planar and the non-planar setting. Moreover, the slope number can also be defined for directed graphs and upward planar drawings. We study upward planar straight-line drawings that use only a constant number of slopes. In particular, for a fixed number $k$ of slopes, we are interested in whether a given directed graph $G$ with maximum in- and outdegree at most $k$ admits an upward planar $k$-slope drawing. We investigate this question both in the fixed and the variable embedding scenario. We show that this problem is in general NP-hard to decide for outerplanar graphs ($k = 3$) and planar graphs ($k \ge 3$). On the positive side, we can decide whether a given cactus graph admits an upward planar $k$-slope drawing and, in the affirmative, construct such a drawing in FPT time with parameter $k$. Furthermore, we can determine the minimum number of slopes required for a given tree in linear time and compute the corresponding drawing efficiently.

cs.CG↗

Coloring Mixed and Directional Interval Graphs

A mixed graph has a set of vertices, a set of undirected egdes, and a set of directed arcs. A proper coloring of a mixed graph $G$ is a function $c$ that assigns to each vertex in $G$ a positive integer such that, for each edge $uv$ in $G$, $c(u) \ne c(v)$ and, for each arc $uv$ in $G$, $c(u) < c(v)$. For a mixed graph $G$, the chromatic number $χ(G)$ is the smallest number of colors in any proper coloring of $G$. A directional interval graph is a mixed graph whose vertices correspond to intervals on the real line. Such a graph has an edge between every two intervals where one is contained in the other and an arc between every two overlapping intervals, directed towards the interval that starts and ends to the right. Coloring such graphs has applications in routing edges in layered orthogonal graph drawing according to the Sugiyama framework; the colors correspond to the tracks for routing the edges. We show how to recognize directional interval graphs, and how to compute their chromatic number efficiently. On the other hand, for mixed interval graphs, i.e., graphs where two intersecting intervals can be connected by an edge or by an arc in either direction arbitrarily, we prove that computing the chromatic number is NP-hard.

cs.DM↗

The Segment Number: Algorithms and Universal Lower Bounds for Some Classes of Planar Graphs

The segment number of a planar graph $G$ is the smallest number of line segments needed for a planar straight-line drawing of $G$. Dujmović, Eppstein, Suderman, and Wood [CGTA'07] introduced this measure for the visual complexity of graphs. There are optimal algorithms for trees and worst-case optimal algorithms for outerplanar graphs, 2-trees, and planar 3-trees. It is known that every cubic triconnected planar $n$-vertex graph (except $K_4$) has segment number $n/2+3$, which is the only known universal lower bound for a meaningful class of planar graphs. We show that every triconnected planar 4-regular graph can be drawn using at most $n+3$ segments. This bound is tight up to an additive constant, improves a previous upper bound of $7n/4+2$ implied by a more general result of Dujmović et al., and supplements the result for cubic graphs. We also give a simple optimal algorithm for cactus graphs, generalizing the above-mentioned result for trees. We prove the first linear universal lower bounds for outerpaths, maximal outerplanar graphs, 2-trees, and planar 3-trees. This shows that the existing algorithms for these graph classes are constant-factor approximations. For maximal outerpaths, our bound is best possible and can be generalized to circular arcs.

cs.CG↗

Consistent Simplification of Polyline Tree Bundles

The Polyline Bundle Simplification (PBS) problem is a generalization of the classical polyline simplification problem. Given a set of polylines, which may share line segments and points, PBS asks for the smallest consistent simplification of these polylines with respect to a given distance threshold. Here, consistent means that each point is either kept in or discarded from all polylines containing it. In previous work, it was proven that PBS is NP-hard to approximate within a factor of $n^{\frac{1}{3}-\varepsilon}$ for any $\varepsilon > 0$ where $n$ denotes the number of points in the input. This hardness result holds even for two polylines. In this paper we first study the practically relevant setting of planar inputs. While for many combinatorial optimization problems the restriction to planar settings makes the problem substantially easier, we show that the inapproximability bound known for general inputs continues to hold even for planar inputs. We proceed with the interesting special case of PBS where the polylines form a rooted tree. Such tree bundles naturally arise in the context of movement data visualization. We prove that optimal simplifications of these tree bundles can be computed in $O(n^3)$ for the Fréchet distance and in $O(n^2)$ for the Hausdorff distance (which both match the computation time for single polylines). Furthermore, we present a greedy heuristic that allows to decompose polyline bundles into tree bundles in order to make our exact algorithm for trees useful on general inputs. The applicability of our approaches is demonstrated in an experimental evaluation on real-world data.

cs.CG↗

Complexity of Scheduling Few Types of Jobs on Related and Unrelated Machines

The task of scheduling jobs to machines while minimizing the total makespan, the sum of weighted completion times, or a norm of the load vector, are among the oldest and most fundamental tasks in combinatorial optimization. Since all of these problems are in general NP-hard, much attention has been given to the regime where there is only a small number $k$ of job types, but possibly the number of jobs $n$ is large; this is the few job types, high-multiplicity regime. Despite many positive results, the hardness boundary of this regime was not understood until now. We show that makespan minimization on uniformly related machines ($Q|HM|C_{\max}$) is NP-hard already with $6$ job types, and that the related Cutting Stock problem is NP-hard already with $8$ item types. For the more general unrelated machines model ($R|HM|C_{\max}$), we show that if either the largest job size $p_{\max}$, or the number of jobs $n$ are polynomially bounded in the instance size $|I|$, there are algorithms with complexity $|I|^{\textrm{poly}(k)}$. Our main result is that this is unlikely to be improved, because $Q||C_{\max}$ is W[1]-hard parameterized by $k$ already when $n$, $p_{\max}$, and the numbers describing the speeds are polynomial in $|I|$; the same holds for $R|HM|C_{\max}$ (without speeds) when the job sizes matrix has rank $2$. Our positive and negative results also extend to the objectives $\ell_2$-norm minimization of the load vector and, partially, sum of weighted completion times $\sum w_j C_j$. Along the way, we answer affirmatively the question whether makespan minimization on identical machines ($P||C_{\max}$) is fixed-parameter tractable parameterized by $k$, extending our understanding of this fundamental problem. Together with our hardness results for $Q||C_{\max}$ this implies that the complexity of $P|HM|C_{\max}$ is the only remaining open case.

cs.DS↗

Erratum: Fast and Simple Horizontal Coordinate Assignment

We point out two flaws in the algorithm of Brandes and Köpf (Proc. GD 2001), which is often used for the horizontal coordinate assignment in Sugiyama's framework for layered layouts. One of them has been noted and fixed multiple times, the other has not been documented before and requires a non-trivial adaptation. On the bright side, neither running time nor extensions of the algorithm are affected adversely.

cs.DS↗

Simplification of Polyline Bundles

We propose and study a generalization to the well-known problem of polyline simplification. Instead of a single polyline, we are given a set of $\ell$ polylines possibly sharing some line segments and bend points. Our goal is to minimize the number of bend points in the simplified bundle with respect to some error tolerance $δ$ (measuring Fréchet distance) but under the additional constraint that shared parts have to be simplified consistently. We show that polyline bundle simplification is NP-hard to approximate within a factor $n^{1/3 - \varepsilon}$ for any $\varepsilon > 0$ where $n$ is the number of bend points in the polyline bundle. This inapproximability even applies to instances with only $\ell=2$ polylines. However, we identify the sensitivity of the solution to the choice of $δ$ as a reason for this strong inapproximability. In particular, we prove that if we allow $δ$ to be exceeded by a factor of $2$ in our solution, we can find a simplified polyline bundle with no more than $O(\log (\ell + n)) \cdot OPT$ bend points in polytime, providing us with an efficient bi-criteria approximation. As a further result, we show fixed-parameter tractability in the number of shared bend points.

cs.CG↗

Recognizing Stick Graphs with and without Length Constraints

Stick graphs are intersection graphs of horizontal and vertical line segments that all touch a line of slope -1 and lie above this line. De Luca et al. [GD'18] considered the recognition problem of stick graphs when no order is given (STICK), when the order of either one of the two sets is given (STICK_A), and when the order of both sets is given (STICK_AB). They showed how to solve STICK_AB efficiently. In this paper, we improve the running time of their algorithm, and we solve STICK_A efficiently. Further, we consider variants of these problems where the lengths of the sticks are given as input. We show that these variants of STICK, STICK_A, and STICK_AB are all NP-complete. On the positive side, we give an efficient solution for STICK_AB with fixed stick lengths if there are no isolated vertices.

cs.CG↗

Compact Drawings of 1-Planar Graphs with Right-Angle Crossings and Few Bends

We study the following classes of beyond-planar graphs: 1-planar, IC-planar, and NIC-planar graphs. These are the graphs that admit a 1-planar, IC-planar, and NIC-planar drawing, respectively. A drawing of a graph is 1-planar if every edge is crossed at most once. A 1-planar drawing is IC-planar if no two pairs of crossing edges share a vertex. A 1-planar drawing is NIC-planar if no two pairs of crossing edges share two vertices. We study the relations of these beyond-planar graph classes (beyond-planar graphs is a collective term for the primary attempts to generalize the planar graphs) to right-angle crossing (RAC) graphs that admit compact drawings on the grid with few bends. We present four drawing algorithms that preserve the given embeddings. First, we show that every $n$-vertex NIC-planar graph admits a NIC-planar RAC drawing with at most one bend per edge on a grid of size $O(n) \times O(n)$. Then, we show that every $n$-vertex 1-planar graph admits a 1-planar RAC drawing with at most two bends per edge on a grid of size $O(n^3) \times O(n^3)$. Finally, we make two known algorithms embedding-preserving; for drawing 1-planar RAC graphs with at most one bend per edge and for drawing IC-planar RAC graphs straight-line.

cs.CG↗

Planar Steiner Orientation is NP-complete

Many applications in graph theory are motivated by routing or flow problems. Among these problems is Steiner Orientation: given a mixed graph G (having directed and undirected edges) and a set T of k terminal pairs in G, is there an orientation of the undirected edges in G such that there is a directed path for every terminal pair in T ? This problem was shown to be NP -complete by Arkin and Hassin [1] and later W [1]-hard by Pilipczuk and Wahlström [7], parametrized by k. On the other hand, there is an XP algorithm by Cygan et al. [3] and a polynomial time algorithm for graphs without directed edges by Hassin and Megiddo [5]. Chitnis and Feldmann [2] showed W [1]-hardness of the problem for graphs of genus 1. We consider a further restriction to planar graphs and show NP -completeness.

cs.DM↗