7,345 research outputs found

    Minimum Convex Partitions and Maximum Empty Polytopes

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    Let SS be a set of nn points in Rd\mathbb{R}^d. A Steiner convex partition is a tiling of conv(S){\rm conv}(S) with empty convex bodies. For every integer dd, we show that SS admits a Steiner convex partition with at most ⌈(n−1)/d⌉\lceil (n-1)/d\rceil tiles. This bound is the best possible for points in general position in the plane, and it is best possible apart from constant factors in every fixed dimension d≥3d\geq 3. We also give the first constant-factor approximation algorithm for computing a minimum Steiner convex partition of a planar point set in general position. Establishing a tight lower bound for the maximum volume of a tile in a Steiner convex partition of any nn points in the unit cube is equivalent to a famous problem of Danzer and Rogers. It is conjectured that the volume of the largest tile is ω(1/n)\omega(1/n). Here we give a (1−ε)(1-\varepsilon)-approximation algorithm for computing the maximum volume of an empty convex body amidst nn given points in the dd-dimensional unit box [0,1]d[0,1]^d.Comment: 16 pages, 4 figures; revised write-up with some running times improve

    On the Number of Maximum Empty Boxes Amidst n Points

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    We revisit the following problem (along with its higher dimensional variant): Given a set S of n points inside an axis-parallel rectangle U in the plane, find a maximum-area axis-parallel sub-rectangle that is contained in U but contains no points of S. 1. We prove that the number of maximum-area empty rectangles amidst n points in the plane is O(n log n 2^alpha(n)), where alpha(n) is the extremely slowly growing inverse of Ackermann\u27s function. The previous best bound, O(n^2), is due to Naamad, Lee, and Hsu (1984). 2. For any d at least 3, we prove that the number of maximum-volume empty boxes amidst n points in R^d is always O(n^d) and sometimes Omega(n^floor(d/2)). This is the first superlinear lower bound derived for this problem. 3. We discuss some algorithmic aspects regarding the search for a maximum empty box in R^3. In particular, we present an algorithm that finds a (1-epsilon)-approximation of the maximum empty box amidst n points in O(epsilon^{-2} n^{5/3} log^2{n}) time
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