Computational complexity is central to computational geometry, with great practical significance if algorithms are used on very large datasets containing tens or hundreds of millions of points. For such sets, the difference between O(n2) and O(n log n) may be the difference between days and seconds of computation.
Computational complexity is central to computational geometry with great practical significance if algorithms are used on very large datasets containing tens or hundreds of millions of points For such sets, the difference between O(n2) and O(n log n) may be the difference between days and seconds of computation