The geometric set cover problem is the special case of the set cover problem in geometric settings. The input is a range space Σ = ( X , R ) {\displaystyle \Sigma =(X,{\mathcal {R}})} where X {\displaystyle X} is a universe of points in R d {\displaystyle \mathbb {R} ^{d}} and R {\displaystyle {\mathcal {R}}} is a family of subsets of X {\displaystyle X} called ranges, defined by the intersection of X {\displaystyle X} and geometric shapes such as disks and axis-parallel rectangles. The goal is to select a minimum-size subset C ⊆ R {\displaystyle {\mathcal {C}}\subseteq {\mathcal {R}}} of ranges such that every point in the universe X {\displaystyle X} is covered by some range in C {\displaystyle {\mathcal {C}}} .
Given the same range space Σ {\displaystyle \Sigma } , a closely related problem is the geometric hitting set problem, where the goal is to select a minimum-size subset H ⊆ X {\displaystyle H\subseteq X} of points such that every range of R {\displaystyle {\mathcal {R}}} has nonempty intersection with H {\displaystyle H} , i.e., is hit by H {\displaystyle H} .
In the one-dimensional case, where X {\displaystyle X} contains points on the real line and R {\displaystyle {\mathcal {R}}} is defined by intervals, both the geometric set cover and hitting set problems can be solved in polynomial time using a simple greedy algorithm. However, in higher dimensions, they are known to be NP-complete even for simple shapes, i.e., when R {\displaystyle {\mathcal {R}}} is induced by unit disks or unit squares. The discrete unit disc cover problem is a geometric version of the general set cover problem which is NP-hard.
Many approximation algorithms have been devised for these problems. Due to the geometric nature, the approximation ratios for these problems can be much better than the general set cover/hitting set problems. Moreover, these approximate solutions can even be computed in near-linear time.