Parameterized Approaches to Orthogonal Compaction

Fuente: arXiv
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Auteurs principaux: Didimo, Walter, Gupta, Siddharth, Kindermann, Philipp, Liotta, Giuseppe, Wolff, Alexander, Zehavi, Meirav
Format: Preprint
Publié: 2022
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author Didimo, Walter
Gupta, Siddharth
Kindermann, Philipp
Liotta, Giuseppe
Wolff, Alexander
Zehavi, Meirav
author_facet Didimo, Walter
Gupta, Siddharth
Kindermann, Philipp
Liotta, Giuseppe
Wolff, Alexander
Zehavi, Meirav
contents Orthogonal graph drawings are used in applications such as UML diagrams, VLSI layout, cable plans, and metro maps. We focus on drawing planar graphs and assume that we are given an \emph{orthogonal representation} that describes the desired shape, but not the exact coordinates of a drawing. Our aim is to compute an orthogonal drawing on the grid that has minimum area among all grid drawings that adhere to the given orthogonal representation. This problem is called orthogonal compaction (OC) and is known to be NP-hard, even for orthogonal representations of cycles [Evans et al., 2022]. We investigate the complexity of OC with respect to several parameters. Among others, we show that OC is fixed-parameter tractable with respect to the most natural of these parameters, namely, the number of \emph{kitty corners} of the orthogonal representation: the presence of pairs of kitty corners in an orthogonal representation makes the OC problem hard. Informally speaking, a pair of kitty corners is a pair of reflex corners of a face that point at each other. Accordingly, the number of kitty corners is the number of corners that are involved in some pair of kitty corners.
format Preprint
id arxiv_https___arxiv_org_abs_2210_05019
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Parameterized Approaches to Orthogonal Compaction
Didimo, Walter
Gupta, Siddharth
Kindermann, Philipp
Liotta, Giuseppe
Wolff, Alexander
Zehavi, Meirav
Computational Geometry
Orthogonal graph drawings are used in applications such as UML diagrams, VLSI layout, cable plans, and metro maps. We focus on drawing planar graphs and assume that we are given an \emph{orthogonal representation} that describes the desired shape, but not the exact coordinates of a drawing. Our aim is to compute an orthogonal drawing on the grid that has minimum area among all grid drawings that adhere to the given orthogonal representation. This problem is called orthogonal compaction (OC) and is known to be NP-hard, even for orthogonal representations of cycles [Evans et al., 2022]. We investigate the complexity of OC with respect to several parameters. Among others, we show that OC is fixed-parameter tractable with respect to the most natural of these parameters, namely, the number of \emph{kitty corners} of the orthogonal representation: the presence of pairs of kitty corners in an orthogonal representation makes the OC problem hard. Informally speaking, a pair of kitty corners is a pair of reflex corners of a face that point at each other. Accordingly, the number of kitty corners is the number of corners that are involved in some pair of kitty corners.
title Parameterized Approaches to Orthogonal Compaction
topic Computational Geometry
url https://arxiv.org/abs/2210.05019