红蓝点分离的参数化复杂度

Q4 Mathematics
Édouard Bonnet, P. Giannopoulos, M. Lampis
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引用次数: 10

摘要

我们研究了以下几何分离问题:给定平面上的红点集合R$和蓝点集合B$,找到一个最小尺寸的直线集将R$和B$分开。我们证明,在它的全部通性中,用解中的行数$k$参数化,这个问题不太可能比暴力破解$n^{O(k)}$时间算法求解得快得多,其中$n$是点的总数。事实上,我们证明了在时间$f(k)n^{o(k/ \log k)}$上运行的算法,对于任何可计算函数$f$,将证明ETH是不成立的。我们的简化关键依赖于从具有大量不同斜率的集合中选择直线(即,这个数字不是k的函数)。假定要求直线与轴线平行的问题变体在直线数上为FPT,我们给出如下初步结果。用一个最小的轴平行线集来分离$R$和$B$的问题在任何一个集合的大小上都是FPT,并且可以在时间$O^*(9^{|B|})$(假设$B$是最小的集合)$中求解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Parameterized Complexity of Red-Blue Points Separation
We study the following geometric separation problem: Given a set $R$ of red points and a set $B$ of blue points in the plane, find a minimum-size set of lines that separate $R$ from $B$. We show that, in its full generality, parameterized by the number of lines $k$ in the solution, the problem is unlikely to be solvable significantly faster than the brute-force $n^{O(k)}$-time algorithm, where $n$ is the total number of points. Indeed, we show that an algorithm running in time $f(k)n^{o(k/ \log k)}$, for any computable function $f$, would disprove ETH. Our reduction crucially relies on selecting lines from a set with a large number of different slopes (i.e., this number is not a function of $k$). Conjecturing that the problem variant where the lines are required to be axis-parallel is FPT in the number of lines, we show the following preliminary result. Separating $R$ from $B$ with a minimum-size set of axis-parallel lines is FPT in the size of either set, and can be solved in time $O^*(9^{|B|})$ (assuming that $B$ is the smallest set).
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
4
审稿时长
>12 weeks
期刊介绍: The International Journal of Computational Geometry & Applications (IJCGA) is a quarterly journal devoted to the field of computational geometry within the framework of design and analysis of algorithms. Emphasis is placed on the computational aspects of geometric problems that arise in various fields of science and engineering including computer-aided geometry design (CAGD), computer graphics, constructive solid geometry (CSG), operations research, pattern recognition, robotics, solid modelling, VLSI routing/layout, and others. Research contributions ranging from theoretical results in algorithm design — sequential or parallel, probabilistic or randomized algorithms — to applications in the above-mentioned areas are welcome. Research findings or experiences in the implementations of geometric algorithms, such as numerical stability, and papers with a geometric flavour related to algorithms or the application areas of computational geometry are also welcome.
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