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https://dx.doi.org/10.48550/ar...
Article . 2018
License: arXiv Non-Exclusive Distribution
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Efficient constant factor approximation algorithms for stabbing line segments with equal disks

Authors: Konstantin Kobylkin;

Efficient constant factor approximation algorithms for stabbing line segments with equal disks

Abstract

An NP-hard problem is considered of intersecting a given set of $n$ straight line segments on the plane with the smallest cardinality set of disks of fixed radii $r>0,$ where the set of segments forms a straight line drawing $G=(V,E)$ of a planar graph without proper edge crossings. To the best of our knowledge, related work only tackles a setting where $E$ consists of (generally, properly overlapping) axis-parallel segments, resulting in an $O(n\log n)$-time and $O(n\log n)$-space 8-approximation algorithm. Exploiting tough connection of the problem with the geometric Hitting Set problem, an $\left(50+52\sqrt{\frac{12}{13}}+��\right)$-approximate $O\left(n^4\log n\right)$-time and $O\left(n^2\log n\right)$-space algorithm is devised based on the modified Agarwal-Pan algorithm, which uses epsilon nets. More accurate $(34+24\sqrt{2}+��)$- and $\left(\frac{144}{5}+32\sqrt{\frac{3}{5}}+��\right)$-approxi\-mate algorithms are also proposed for cases where $G$ is any subgraph of either a generalized outerplane graph or a Delaunay triangulation respectively, which work within the same time and space complexity bounds, where $��>0$ is an arbitrarily small constant.

31 pages

Keywords

Computational Geometry (cs.CG), FOS: Computer and information sciences, Computer Science - Computational Geometry

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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