An Optimal Algorithm for Half-plane Hitting Set
Gang Liu, Haitao Wang
TL;DR
The paper addresses the half-plane hitting set problem for a set $P$ of $n$ points and a set $H$ of $n$ half-planes, seeking a smallest subset of points that hits every half-plane. It introduces a reduction to a circular-point coverage problem on a unit circle, where each half-plane defines a circle point and each $p\in P$ yields a small set of arcs on the circle; an optimal arc cover corresponds to a minimum hitting set. A key insight is that only a subset $\hat{\mathcal{A}}$ of at most $4n$ arcs suffices, and these arcs can be computed in $O(n \log n)$ time, allowing the circular-point coverage subproblem to be solved in $O(n \log n)$ time. Consequently, the overall half-plane hitting set problem is solved in $O(n \log n)$ time, matching the algebraic decision tree lower bound and offering a simpler, near-optimal approach.
Abstract
Given a set $ P $ of $n$ points and a set $ H $ of $n$ half-planes in the plane, we consider the problem of computing a smallest subset of points such that each half-plane contains at least one point of the subset. The previously best algorithm solves the problem in $O(n^3 \log n)$ time. It is also known that $Ω(n \log n)$ is a lower bound for the problem under the algebraic decision tree model. In this paper, we present an $O(n \log n)$ time algorithm, which matches the lower bound and thus is optimal. Another virtue of the algorithm is that it is relatively simple.
