单位平方可见性图的组合性质与识别。

IF 0.6 3区 数学 Q4 COMPUTER SCIENCE, THEORY & METHODS
Discrete & Computational Geometry Pub Date : 2023-01-01 Epub Date: 2023-03-22 DOI:10.1007/s00454-022-00414-8
Katrin Casel, Henning Fernau, Alexander Grigoriev, Markus L Schmid, Sue Whitesides
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引用次数: 0

摘要

单位正方形可见性图(USV)是通过放置在平面中的单位正方形之间的轴平行可见性来描述的。如果需要将正方形放置在整数网格坐标上,则USV变为单位正方形网格可见性图(USGV),这是众所周知的直线图的另一种特征。我们扩展了USGV的已知组合结果,并表明,在弱情况下(即,可见性不一定转化为所表示的组合图的边),其识别问题的面积最小化变体是NP困难的。我们还提供了关于USV的组合见解,作为我们的主要结果,我们证明了它们的识别问题是NP难的,这解决了一个悬而未决的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Combinatorial Properties and Recognition of Unit Square Visibility Graphs.

Combinatorial Properties and Recognition of Unit Square Visibility Graphs.

Combinatorial Properties and Recognition of Unit Square Visibility Graphs.

Combinatorial Properties and Recognition of Unit Square Visibility Graphs.

Unit square visibility graphs (USV) are described by axis-parallel visibility between unit squares placed in the plane. If the squares are required to be placed on integer grid coordinates, then USV become unit square grid visibility graphs (USGV), an alternative characterisation of the well-known rectilinear graphs. We extend known combinatorial results for USGV and we show that, in the weak case (i.e., visibilities do not necessarily translate into edges of the represented combinatorial graph), the area minimisation variant of their recognition problem is NP-hard. We also provide combinatorial insights with respect to USV, and as our main result, we prove their recognition problem to be NP-hard, which settles an open question.

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来源期刊
Discrete & Computational Geometry
Discrete & Computational Geometry 数学-计算机:理论方法
CiteScore
1.80
自引率
12.50%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Discrete & Computational Geometry (DCG) is an international journal of mathematics and computer science, covering a broad range of topics in which geometry plays a fundamental role. It publishes papers on such topics as configurations and arrangements, spatial subdivision, packing, covering, and tiling, geometric complexity, polytopes, point location, geometric probability, geometric range searching, combinatorial and computational topology, probabilistic techniques in computational geometry, geometric graphs, geometry of numbers, and motion planning.
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