16 research outputs found
Parameterized Algorithms for Queue Layouts
An -queue layout of a graph consists of a linear order of its vertices
and a partition of its edges into queues, such that no two independent
edges of the same queue nest. The minimum such that admits an -queue
layout is the queue number of . We present two fixed-parameter tractable
algorithms that exploit structural properties of graphs to compute optimal
queue layouts. As our first result, we show that deciding whether a graph
has queue number and computing a corresponding layout is fixed-parameter
tractable when parameterized by the treedepth of . Our second result then
uses a more restrictive parameter, the vertex cover number, to solve the
problem for arbitrary .Comment: Appears in the Proceedings of the 28th International Symposium on
Graph Drawing and Network Visualization (GD 2020
Grundy Distinguishes Treewidth from Pathwidth
Structural graph parameters, such as treewidth, pathwidth, and clique-width,
are a central topic of study in parameterized complexity. A main aim of
research in this area is to understand the "price of generality" of these
widths: as we transition from more restrictive to more general notions, which
are the problems that see their complexity status deteriorate from
fixed-parameter tractable to intractable? This type of question is by now very
well-studied, but, somewhat strikingly, the algorithmic frontier between the
two (arguably) most central width notions, treewidth and pathwidth, is still
not understood: currently, no natural graph problem is known to be W-hard for
one but FPT for the other. Indeed, a surprising development of the last few
years has been the observation that for many of the most paradigmatic problems,
their complexities for the two parameters actually coincide exactly, despite
the fact that treewidth is a much more general parameter. It would thus appear
that the extra generality of treewidth over pathwidth often comes "for free".
Our main contribution in this paper is to uncover the first natural example
where this generality comes with a high price. We consider Grundy Coloring, a
variation of coloring where one seeks to calculate the worst possible coloring
that could be assigned to a graph by a greedy First-Fit algorithm. We show that
this well-studied problem is FPT parameterized by pathwidth; however, it
becomes significantly harder (W[1]-hard) when parameterized by treewidth.
Furthermore, we show that Grundy Coloring makes a second complexity jump for
more general widths, as it becomes para-NP-hard for clique-width. Hence, Grundy
Coloring nicely captures the complexity trade-offs between the three most
well-studied parameters. Completing the picture, we show that Grundy Coloring
is FPT parameterized by modular-width.Comment: To be published in proceedings of ESA 202
A Unifying Framework for Characterizing and Computing Width Measures
Algorithms for computing or approximating optimal decompositions for decompositional parameters such as treewidth or clique-width have so far traditionally been tailored to specific width parameters. Moreover, for mim-width, no efficient algorithms for computing good decompositions were known, even under highly restrictive parameterizations. In this work we identify ?-branchwidth as a class of generic decompositional parameters that can capture mim-width, treewidth, clique-width as well as other measures. We show that while there is an infinite number of ?-branchwidth parameters, only a handful of these are asymptotically distinct. We then develop fixed-parameter and kernelization algorithms (under several structural parameterizations) that can approximate every possible ?-branchwidth, providing a unifying parameterized framework that can efficiently obtain near-optimal tree-decompositions, k-expressions, as well as optimal mim-width decompositions
Parameterized Algorithms and Data Reduction for Safe Convoy Routing
We study a problem that models safely routing a convoy through a transportation network, where any vertex adjacent to the travel path of the convoy requires additional precaution: Given a graph G=(V,E), two vertices s,t in V, and two integers k,l, we search for a simple s-t-path with at most k vertices and at most l neighbors. We study the problem in two types of transportation networks: graphs with small crossing number, as formed by road networks, and tree-like graphs, as formed by waterways. For graphs with constant crossing number, we provide a subexponential 2^O(sqrt n)-time algorithm and prove a matching lower bound. We also show a polynomial-time data reduction algorithm that reduces any problem instance to an equivalent instance (a so-called problem kernel) of size polynomial in the vertex cover number of the input graph. In contrast, we show that the problem in general graphs is hard to preprocess. Regarding tree-like graphs, we obtain a 2^O(tw) * l^2 * n-time algorithm for graphs of treewidth tw, show that there is no problem kernel with size polynomial in tw, yet show a problem kernel with size polynomial in the feedback edge number of the input graph
Slim Tree-Cut Width
Tree-cut width is a parameter that has been introduced as an attempt to obtain an analogue of treewidth for edge cuts. Unfortunately, in spite of its desirable structural properties, it turned out that tree-cut width falls short as an edge-cut based alternative to treewidth in algorithmic aspects. This has led to the very recent introduction of a simple edge-based parameter called edge-cut width [WG 2022], which has precisely the algorithmic applications one would expect from an analogue of treewidth for edge cuts, but does not have the desired structural properties.
In this paper, we study a variant of tree-cut width obtained by changing the threshold for so-called thin nodes in tree-cut decompositions from 2 to 1. We show that this "slim tree-cut width" satisfies all the requirements of an edge-cut based analogue of treewidth, both structural and algorithmic, while being less restrictive than edge-cut width. Our results also include an alternative characterization of slim tree-cut width via an easy-to-use spanning-tree decomposition akin to the one used for edge-cut width, a characterization of slim tree-cut width in terms of forbidden immersions as well as an approximation algorithm for computing the parameter
On the computational tractability of a geographic clustering problem arising in redistricting
Redistricting is the problem of dividing a state into a number of
regions, called districts. Voters in each district elect a representative. The
primary criteria are: each district is connected, district populations are
equal (or nearly equal), and districts are "compact". There are multiple
competing definitions of compactness, usually minimizing some quantity.
One measure that has been recently promoted by Duchin and others is number of
cut edges. In redistricting, one is given atomic regions out of which each
district must be built. The populations of the atomic regions are given.
Consider the graph with one vertex per atomic region (with weight equal to the
region's population) and an edge between atomic regions that share a boundary.
A districting plan is a partition of vertices into parts, each connnected,
of nearly equal weight. The districts are considered compact to the extent that
the plan minimizes the number of edges crossing between different parts.
Consider two problems: find the most compact districting plan, and sample
districting plans under a compactness constraint uniformly at random. Both
problems are NP-hard so we restrict the input graph to have branchwidth at most
. (A planar graph's branchwidth is bounded by its diameter.) If both and
are bounded by constants, the problems are solvable in polynomial time.
Assume vertices have weight~1. One would like algorithms whose running times
are of the form for some constant independent of and
, in which case the problems are said to be fixed-parameter tractable with
respect to and ). We show that, under a complexity-theoretic assumption,
no such algorithms exist. However, we do give algorithms with running time
. Thus if the diameter of the graph is moderately small and the
number of districts is very small, our algorithm is useable