Three problems about simple polygons

We give three related algorithmic results concerning a simple polygon P:

1. Improving a series of previous work, we show how to find a largest pair of disjoint congruent disks inside P in linear expected time.

2. As a subroutine for the above result, we show how to find the convex hull of any given subset of the vertices of P in linear worst-case time.

3. More generally, we show how to compute a triangulation of any given subset of the vertices or edges of P in almost linear time.

I/O-efficient algorithms for computing planar geometric spanners

We present I/O-efficient algorithms for computing planar Steiner spanners for point sets and sets of polygonal obstacles in the plane.     

Reconstructing under Group Actions

We give a bound on the reconstructibility of an action GX in terms of the reconstructibility of a the action NX, where N is a normal subgroup of G, and the reconstructibility of the quotient G/N. We also show that if the action GX is locally finite, in the sense that every point is either in an orbit by itself or has finite stabilizer, then the reconstructibility of GX is at most the reconstructibility of G. Finally, we give some applications to geometric reconstruction problems.     

Regular Steiner polygons

The symmetric difference area functional is minimized for a pair of planar convex polygons. Two solution procedures are outlined: a direct constructive methodology and a support function formulation. Examples illustrate the solution methodology.     

Computing simple paths among obstacles

Given a set X of points in the plane, two distinguished points s,tX, and a set Φ of obstacles represented by line segments, we wish to compute a simple polygonal path from s to t that uses only points in X as vertices and avoids the obstacles in Φ. We present two results: (1) we show that finding such simple paths among arbitrary obstacles is NP-complete, and (2) we give a polynomial-time algorithm that computes simple paths when the obstacles form a simple polygon P and X is inside P. Our algorithm runs in time O(m²n²), where m is the number of vertices of P and n is the number of points in X.     

LOOK: A Lazy Object-Oriented Kernel design for geometric computation

In this paper we describe and discuss a new kernel design for geometric computation in the plane. It combines different kinds of floating-point filter techniques and a lazy evaluation scheme with the exact number types provided by LEDA allowing for efficient and exact computation with rational and algebraic geometric objects.

It is the first kernel design which uses floating-point filter techniques on the level of geometric constructions.

The experiments we present—partly using the CGAL framework—show a great improvement in speed and—maybe even more important for practical applications—memory consumption when dealing with more complex geometric computations.     

On some geometric optimization problems in layered manufacturing

Efficient geometric algorithms are given for optimization problems arising in layered manufacturing, where a 3D object is built by slicing its CAD model into layers and manufacturing the layers successively. The problems considered include minimizing the stair-step error on the surfaces of the manufactured object under various formulations, minimizing the volume of the so-called support structures used, and minimizing the contact area between the supports and the manufactured object—all of which are factors that affect the speed and accuracy of the process. The stair-step minimization algorithm is valid for any polyhedron, while the support minimization algorithms are applicable only to convex polyhedra. The techniques used to obtain these results include construction and searching of certain arrangements on the sphere, 3D convex hulls, halfplane range searching, and constrained optimization.     

The point in polygon problem for arbitrary polygons

A detailed discussion of the point in polygon problem for arbitrary polygons is given. Two concepts for solving this problem are known in literature: the even–odd rule and the winding number, the former leading to ray-crossing, the latter to angle summation algorithms. First we show by mathematical means that both concepts are very closely related, thereby developing a first version of an algorithm for determining the winding number. Then we examine how to accelerate this algorithm and how to handle special cases. Furthermore we compare these algorithms with those found in literature and discuss the results.     

Structural filtering: a paradigm for efficient and exact geometric programs

We introduce a new and simple filtering technique that can be used in the implementation of geometric algorithms called “structural filtering”. Using this filtering technique we gain about 20% when compared to predicate-filtered implementations. Of theoretical interest are some results regarding the robustness of sorting algorithms against erroneous comparisons.

There is software support for the concept of structural filtering in LEDA (Library of Efficient Data Types and Algorithms, http://www.mpi-sb.mpg.de/LEDA/leda.html) and CGAL (Computational Geometry Algorithms Library, http://www.cgal.org).     

A geometric proof of the combinatorial bounds for the number of optimal solutions for the Euclidean 2-center problem

We provide lower and upper bounds for γ(n), the number of optimal solutions for the two-center problem: “Given a set S of n points in the real plane, find two closed discs whose union contains all of the points such that the radius of the larger disc is minimized.”The main result of the paper shows the matching upper and lower bounds for the two-center problem and demonstrates that γ(n)=n.     

Computational aspects of cutting-plane algorithms for geometric programming problems

This paper presents the results of computational studies of the properties of cutting plane algorithms as applied to posynomial geometric programs. The four cutting planes studied represent the gradient method of Kelley and an extension to develop tangential cuts; the geometric inequality of Duffin and an extension to generate several cuts at each iteration. As a result of over 200 problem solutions, we will draw conclusions regarding the effectiveness of acceleration procedures, feasible and infeasible starting point, and the effect of the initial bounds on the variables. As a result of these experiments, certain cutting plane methods are seen to be attractive means of solving large scale geometric programs.This author's research was supported in part by the Center for the Study of Environmental Policy, The Pennsylvania State University.     

Searching for mobile intruders in circular corridors by two 1-searchers

We consider the problem of searching for a mobile intruder in a circular corridor by two mobile searchers, who hold one flashlight. A circular corridor is a polygon with one polygonal hole such that its outer and inner boundaries are mutually weakly visible. Both 1-searchers always direct their flashlights at the inner boundary. The objective is to decide whether there exists a search schedule for two 1-searchers to detect the intruder, no matter how fast he moves, and if so, generate a search schedule. We give a characterization of the circular corridors, which are searchable by two 1-searchers. Based on our characterization, an O(nlogn) time algorithm is then presented to determine the searchability of a circular corridor, where n denotes the total number of vertices of the outer and inner boundaries. Moreover, a search schedule can be reported in time linear in its size, if it exists.     

Approximation algorithms for art gallery problems in polygons

In this paper, we present approximation algorithms for minimum vertex and edge guard problems for polygons with or without holes with a total of n vertices. For simple polygons, approximation algorithms for both problems run in O(n⁴) time and yield solutions that can be at most O(logn) times the optimal solution. For polygons with holes, approximation algorithms for both problems give the same approximation ratio of O(logn), but the running time of the algorithms increases by a factor of n to O(n⁵).     

Lower bounds for computing geometric spanners and approximate shortest paths

We consider the problems of constructing geometric spanners, possibly containing Steiner points, for a set of n input points in d-dimensional space , and constructing spanners and approximate shortest paths among a collection of polygonal obstacles on the plane. The complexities of these problems are shown to be Ω(n log n) in the algebraic computation tree model. Since O(n log n)-time algorithms are known for solving these problems, our lower bounds are tight up to a constant factor.     

Minimum weight pseudo-triangulations

We consider the problem of computing a minimum weight pseudo-triangulation of a set of n points in the plane. We first present an -time algorithm that produces a pseudo-triangulation of weight which is shown to be asymptotically worst-case optimal, i.e., there exists a point set for which every pseudo-triangulation has weight , where is the weight of a minimum weight spanning tree of . We also present a constant factor approximation algorithm running in cubic time. In the process we give an algorithm that produces a minimum weight pseudo-triangulation of a simple polygon.     

Algebraic methods and arithmetic filtering for exact predicates on circle arcs

The purpose of this paper is to present a new method to design exact geometric predicates in algorithms dealing with curved objects such as circular arcs. We focus on the comparison of the abscissae of two intersection points of circle arcs, which is known to be a difficult predicate involved in the computation of arrangements of circle arcs. We present an algorithm for deciding the x-order of intersections from the signs of the coefficients of a polynomial, obtained by a general approach based on resultants. This method allows the use of efficient arithmetic and filtering techniques leading to fast implementation as shown by the experimental results.     

An updated geometric build-up algorithm for solving the molecular distance geometry problems with sparse distance data

An updated geometric build-up algorithm is developed for solving the molecular distance geometry problem with a sparse set of inter-atomic distances. Different from the general geometric build-up algorithm, the updated algorithm re-computes the coordinates of the base atoms whenever necessary and possible. In this way, the errors introduced in solving the algebraic equations for the determination of the coordinates of the atoms are controlled in the intermediate computational steps. The method for re-computing the coordinates of the base atoms based on the estimation on the root-mean-square deviation (RMSD) is described. The results of applying the updated algorithm to a set of protein structure problems are presented. In many cases, the updated algorithm solves the problems with high accuracy when the results of the general algorithm are inadequate.