The congestion of a curve is a measure of how much it zigzags around locally. More precisely, a curve $\pi$ is $c$-packed if the length of the curve lying inside any ball is at most $c$ times the radius of the ball, and its congestion is the maximum $c$ for which $\pi$ is $c$-packed. This paper presents a randomized $(288+\varepsilon)$-approximation algorithm for computing the congestion of a curve (or any set of segments in constant dimension). It runs in $O( n \log^2 n)$ time and succeeds with high probability. Although the approximation factor is large, the running time improves over the previous fastest constant approximation algorithm \cite{gsw-appc-20}, which runs in (roughly) $O(n^{4/3})$ time. We carefully combine new ideas with known techniques to obtain our new, near-linear time algorithm.
翻译:曲线的拥堵度是计算曲线( 或固定维度中的任何一组区段) 拥堵量的尺度。 更确切地说, 曲线$pi 美元是包装在$O ( n log2 n) 中, 如果任何球内曲线的长度是球半径的最多一美元, 而它的拥堵是最大一美元, 而对于它来说, 美元是 $c$ 包装的。 本文为计算曲线( 288 ⁇ varepsilon) 的拥堵量提供了随机化的 $( 288 ⁇ varepsilon) $- apprum 算法 。 它以$O ( n log2 n) 时间和 成功概率很高的方式运行 。 尽管近似系数很大, 运行时间比之前最快的恒定的近似值算法 \ cite {gsw- apc-20} 有所改进 。 我们仔细地将新想法与已知的技术结合起来, 以便获得我们新的近线上的时间算法。