COMPUTATIONAL ASPECTS OF HELLY’S THEOREM AND ITS RELATIVES
David Avis, Michael E. Houle
Abstract
David Avis, Michael E. Houle
Abstract
This paper investigates computational aspects of the well-known convexity theorem due to Helly, which states that the existence of a point in the common intersection of n convex sets is guaranteed by the existence of points in the common intersection of each combination of d+1 of these sets. Given an oracle which accepts d+1 convex sets and either returns a point in their common intersection, or reports its non-existence, we give two algorithms which compute a point in the common intersection of n such gets. The first algorithm runs in O(nd+1T) time and O(nd) space, where T is the time required for a single call to the oracle. The second algorithm is a multi-stage variant of the first by which the space complexity may be reduced to O(n) at the expense of an increase in the time complexity by a factor independent of n. We also show how these algorithms may be adapted to construct linear and spherical separators of a collection of sets, and to construct a translate of a given object which either contains, is contained by, or intersects a collection of convex sets.
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This paper investigates computational aspects of the well-known convexity theorem due to Helly, which states that the existence of a point in the common intersection of n convex sets is guaranteed by the existence of points in the common intersection of each combination of d+1 of these sets. Given an oracle which accepts d+1 convex sets and either returns a point in their common intersection, or reports its non-existence, we give two algorithms which compute a point in the common intersection of n such gets. The first algorithm runs in O(nd+1T) time and O(nd) space, where T is the time required for a single call to the oracle. The second algorithm is a multi-stage variant of the first by which the space complexity may be reduced to O(n) at the expense of an increase in the time complexity by a factor independent of n. We also show how these algorithms may be adapted to construct linear and spherical separators of a collection of sets, and to construct a translate of a given object which either contains, is contained by, or intersects a collection of convex sets.
Key concepts: Intersection (aeronautics), Mathematics, Combinatorics, Convexity, Oracle, Regular polygon, Point (geometry), Construct (python library)