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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.

An Optimal Algorithm for Half-plane Hitting Set

TL;DR

The paper addresses the half-plane hitting set problem for a set of points and a set of 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 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 of at most arcs suffices, and these arcs can be computed in time, allowing the circular-point coverage subproblem to be solved in time. Consequently, the overall half-plane hitting set problem is solved in time, matching the algebraic decision tree lower bound and offering a simpler, near-optimal approach.

Abstract

Given a set of points and a set of 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 time. It is also known that is a lower bound for the problem under the algebraic decision tree model. In this paper, we present an time algorithm, which matches the lower bound and thus is optimal. Another virtue of the algorithm is that it is relatively simple.
Paper Structure (18 sections, 5 theorems, 4 figures)

This paper contains 18 sections, 5 theorems, 4 figures.

Key Result

Lemma 1

$B$ can be covered by $k$ arcs of $\mathcal{A}$ if and only if $H$ can be hit by $k$ points of $P$.

Figures (4)

  • Figure 1: Illustration of $h_{i-1,i}$, $h_{i,i+1}$, and $\rho$.
  • Figure 2: Illustration of the relative positions of the four arcs of $\hat{A}(p)$. The red points are all on the upper half circle $C_u$ while the blue points are all on the lower half circle $C_l$.
  • Figure 3: Illustration of the definition of $H^*_l[i_p,j_p]$ when $\ell_p$ contains an edge $e$ of $\mathcal{U}$. $i_p$ and $j_p$ in the figure represent the points $h^*_{i_p}$ and $h^*_{j_p}$, respectively.
  • Figure 4: Illustration of the definition of $H^*_l[i_p,j_p]$ when $\ell_p$ does not contain an edge of $\mathcal{U}$. $i_p$ and $j_p$ in the figure represent the points $h^*_{i_p}$ and $h^*_{j_p}$, respectively.

Theorems & Definitions (9)

  • Lemma 1
  • proof
  • Corollary 1
  • proof
  • Lemma 2
  • proof
  • Lemma 3
  • proof
  • Theorem 1