4 research outputs found
Advances on Testing C-Planarity of Embedded Flat Clustered Graphs
We show a polynomial-time algorithm for testing c-planarity of embedded flat
clustered graphs with at most two vertices per cluster on each face.Comment: Accepted at GD '1
Subexponential-Time and FPT Algorithms for Embedded Flat Clustered Planarity
The C-Planarity problem asks for a drawing of a ,
i.e., a graph whose vertices belong to properly nested clusters, in which each
cluster is represented by a simple closed region with no edge-edge crossings,
no region-region crossings, and no unnecessary edge-region crossings. We study
C-Planarity for , graphs with a fixed
combinatorial embedding whose clusters partition the vertex set. Our main
result is a subexponential-time algorithm to test C-Planarity for these graphs
when their face size is bounded. Furthermore, we consider a variation of the
notion of in which, for each face,
including the outer face, there is a bag that contains every vertex of the
face. We show that C-Planarity is fixed-parameter tractable with the
embedded-width of the underlying graph and the number of disconnected clusters
as parameters.Comment: 14 pages, 6 figure
Constrained Planarity in Practice -- Engineering the Synchronized Planarity Algorithm
In the constrained planarity setting, we ask whether a graph admits a planar
drawing that additionally satisfies a given set of constraints. These
constraints are often derived from very natural problems; prominent examples
are Level Planarity, where vertices have to lie on given horizontal lines
indicating a hierarchy, and Clustered Planarity, where we additionally draw the
boundaries of clusters which recursively group the vertices in a crossing-free
manner. Despite receiving significant amount of attention and substantial
theoretical progress on these problems, only very few of the found solutions
have been put into practice and evaluated experimentally.
In this paper, we describe our implementation of the recent quadratic-time
algorithm by Bl\"asius et al. [TALG Vol 19, No 4] for solving the problem
Synchronized Planarity, which can be seen as a common generalization of several
constrained planarity problems, including the aforementioned ones. Our
experimental evaluation on an existing benchmark set shows that even our
baseline implementation outperforms all competitors by at least an order of
magnitude. We systematically investigate the degrees of freedom in the
implementation of the Synchronized Planarity algorithm for larger instances and
propose several modifications that further improve the performance. Altogether,
this allows us to solve instances with up to 100 vertices in milliseconds and
instances with up to 100 000 vertices within a few minutes.Comment: to appear in Proceedings of ALENEX 202
Computing maximum c-planar subgraphs
Abstract. Deciding c-planarity for a given clustered graph C = (G, T) is one of the most challenging problems in current graph drawing research. Though it is yet unknown if this problem is solvable in polynomial time, latest research focused on algorithmic approaches for special classes of clustered graphs. In this paper, we introduce an approach to solve the general problem using integer linear programming (ILP) techniques. We give an ILP formulation that also includes the natural generalization of c-planarity testing—the maximum c-planar subgraph problem—and solve this ILP with a branch-and-cut algorithm. Our computational results show that this approach is already successful for many clustered graphs of small to medium sizes and thus can be the foundation of a practically efficient algorithm that integrates further sophisticated ILP techniques.