Optimal Algorithms for Some Intersection Radius Problems

Abstract --Zusammenfassung Optimal Algorithms for Some Intersection Radius Problems. The intersection radius of a set of n geometrical objects in a d-dimensional Euclidean space, E d, is the radius of the smallest closed hypersphere that intersects all the objects of the set. In this paper, we describe optimal algorithms for some intersection radius problems. We first present a linear-time algorithm to determine the smallest closed hypcrsphere that intersects a set of hyperplanes in E ~, assuming d to be a fixed parameter. This is done by reducing the problem to a linear programming problem in a (d + 1)-dimensional space, involving 2n linear constraints. We also show how the prune-and-search technique, coupled with the strategy of replacing a ray by a point or a line can be used to solve, in linear time, the intersection radius problem for a set of n line segments in the plane. Currently, no algorithms are known that solve these intersection radius problems within the same time bounds. AM

Approximation Algorithms for Geometric Clustering and Touring Problems

Clustering and touring are two fundamental topics in optimization that have been studied extensively and have ``launched a thousand ships''. In this thesis, we study variants of these problems for Euclidean instances, in which clusters often correspond to sensors that are required to cover, measure or localize targets and tours need to visit locations for the purpose of item delivery or data collection. In the first part of the thesis, we focus on the task of sensor placement for environments in which localization is a necessity and in which its quality depends on the relative angle between the target and the pair of sensors observing it. We formulate a new coverage constraint that bounds this angle and consider the problem of placing a small number of sensors that satisfy it in addition to classical ones such as proximity and line-of-sight visibility. We present a general framework that chooses a small number of sensors and approximates the coverage constraint to arbitrary precision. In the second part of the thesis, we consider the task of collecting data from a set of sensors by getting close to them. This corresponds to a well-known generalization of the Traveling Salesman Problem (TSP) called TSP with Neighborhoods, in which we want to compute a shortest tour that visits at least one point from each unit disk centered at a sensor. One approach is based on an observation that relates the optimal solution with the optimal TSP on the sensors. We show that the associated bound can be improved unless we are in certain exceptional circumstances for which we can get better algorithms. Finally, we discuss Maximum Scatter TSP, which asks for a tour that maximizes the length of the shortest edge. While the Euclidean version admits an efficient approximation scheme and the problem is known to be NP-hard in three dimensions or higher, the question of getting a polynomial time algorithm for two dimensions remains open. To this end, we develop a general technique for the case of points concentrated around the boundary of a circle that we believe can be extended to more general cases

Computing Shortest Transversals

We present an O(n log² n) time and O(n) space algorithm for computing the shortest line segment that intersects a set of n given line segments or lines in the plane. If the line segments do not intersect the algorithm may be trimmed to run in O(n log n) time. Furthermore, in combination with linear programming the algorithm will also find the shortest line segment that intersects a set of n isothetic rectangles in the plane in O(n log k) time, where k is the combinatorial complexity of the space of transversals and k 4n. These results find application in: (1) line-fitting between a set of n data ranges where it is desired to obtain the shortest line-of-fit, (2) finding the shortest line segment from which a convex n-vertex polygon is weakly externally visible, and (3) determining the shortest line-of-sight between two edges of a simple n-vertex polygon, for which O(n) time algorithms are also given. All the algorithms are based on the solution to a new fundamental geometric optim..