扩散点的核化

F. Fomin, P. Golovach, Tanmay Inamdar, Saket Saurabh, M. Zehavi
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引用次数: 1

摘要

我们考虑以下关于分散点的问题。给定平面上的一组点,任务是确定是否通过移动少量点的小距离,我们可以得到点的排列,使得没有一对点彼此“接近”。更准确地说,对于$n$点,一个整数$k$和一个实数$d>0$,我们问是否最多$k$点可以被重新定位,每个点离其原始位置的距离最多$d$,使得每对点之间的距离至少是一个固定常数,例如$1$。对于这个问题的变体,有许多近似算法,在不同的名称下,如遥远的代表,磁盘分散或点扩散,在文献中是已知的。然而,据我们所知,这个问题的参数化复杂性仍然广泛未被探索。我们向这个方向迈出了第一步,提供了一个核化算法,该算法在多项式时间内产生一个具有$O(d^2k^3)$点的等效实例。作为这个结果的副产品,我们也为这个问题设计了一个非平凡的固定参数可处理(FPT)算法,参数化为$k$和$d$。最后,我们通过给出一个下界来补充关于多项式核化的结果,该下界排除了在$k$中单独存在一个大小为多项式的核,除非$\mathsf{NP} \subseteq \mathsf{coNP}/\text{poly}$。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kernelization for Spreading Points
We consider the following problem about dispersing points. Given a set of points in the plane, the task is to identify whether by moving a small number of points by small distance, we can obtain an arrangement of points such that no pair of points is ``close"to each other. More precisely, for a family of $n$ points, an integer $k$, and a real number $d>0$, we ask whether at most $k$ points could be relocated, each point at distance at most $d$ from its original location, such that the distance between each pair of points is at least a fixed constant, say $1$. A number of approximation algorithms for variants of this problem, under different names like distant representatives, disk dispersing, or point spreading, are known in the literature. However, to the best of our knowledge, the parameterized complexity of this problem remains widely unexplored. We make the first step in this direction by providing a kernelization algorithm that, in polynomial time, produces an equivalent instance with $O(d^2k^3)$ points. As a byproduct of this result, we also design a non-trivial fixed-parameter tractable (FPT) algorithm for the problem, parameterized by $k$ and $d$. Finally, we complement the result about polynomial kernelization by showing a lower bound that rules out the existence of a kernel whose size is polynomial in $k$ alone, unless $\mathsf{NP} \subseteq \mathsf{coNP}/\text{poly}$.
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