43 research outputs found

    Approximative Terrain Guarding with Given Number of Guards

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    Guarding a surface is a well known optimization problem of the visibility site analysis and has many applications. The basic problem is searching for the minimum number of guards needed to guard (see) the entire surface. More realistic is the guarding where the number of guards is upward limited and the optimization problem is to search for their locations in order to guard as much surface as possible. In the paper this problem is treated in detail. Several known heuristics (greedy add, greedy add with swap and stingy drop) are revised and a new technique called solution improving technique is proposed. The technique improves the results of the known algorithms and is used in indirect solving of the problem. Tests on 44 DEMs from USGS DEM Repository showed that our technique yields comparative results for smaller number of guards and better results for higher number of guards

    A New Approach for Vertex Guarding of Planar Graphs

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    Vertex guarding is one of many optimisation problems in graph theory with wide area of applications. It is proven to be NP-hard, therefore fast approximative solutions are significant. In the paper, at first, known algorithms are considered, and then a new algorithm working on planar graphs is introduced. The new algorithm is based on the dynamic approach and produces better and faster solutions. Its efficiency among other algorithms is demonstrated experimentally. In addition, ideas to additionally improve the algorithm are presented at the end

    Geometric optimization and querying : exact & approximate

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    This thesis has two main parts. The first part deals with the stage illumination problem. Given a stage represented by a line segment L and a set of lightsources represented by a set of points S in the plane, assign powers to the lightsources such that every point on the stage receives a sufficient amount, e.g. one unit, of light while minimizing the overall power consumption. By assuming that the amount of light arriving from a fixed lightsource decreases rapidly with the distance from the lightsource, this becomes an interesting geometric optimization problem. We present different solutions, based on convex optimization, discretization and linear programming, as well as a purely combinatorial approximation algorithm. Some experimental results are also provided. In the second part of this thesis, we are concerned with two different geometric problems whose solutions are based on the construction of a data structure that would allow for efficient queries. The central idea of our data structures is the well-separated pair decomposition. The first problem we address is the k-hop restricted shortest path under the power-euclidean distance function. Given a set P of n points in the plane and the distance function jpqjd +Cp for some constant d > 1, nonnegative offset cost Cp and p;q 2 P, where jpqj denotes the Euclidean distance between p and q, we consider the problem of finding paths between any pair of points that minimize the lenght of the path and do not use more than some constant number k of hops. Known exact algorithms for this problem required W(nlogn) per query pair (p;q). We relax the exactness requirement and only require approximate (1+e) solutions which allows us to derive schemes which guarantee constant query time using linear space and O(nlogn) preprocessing time. The dependence on e is polynomial in 1=e. We also develop a tool that might be of independent interest: For any pair of points p;q 2 P report in constant time the cluster pair (A;B) representing (p;q) in a well-separated pair decomposition of P. The second problem in this part is so-called cone-restricted nearest neighbor. For a given point set in Euclidean space we consider the problem of finding (approximate) nearest neighbors of a query point but restricting only to points that lie within a fixed cone with apex at the query point. We investigate the structure of the Voronoi diagram induced by this notion of proximity and present approximate and exact data structures for answering cone-restricted nearest neighbor queries. In particular, we develop an approximate Voronoi diagram of size O((n=ed) log(1=e)) that can be used to answer cone-restricted nearest neighbor queries in O(log(n=e)) time.Diese Arbeit besteht aus zwei Teilen. Der erste Teil behandelt das Stage Illumination Problem. Hierbei möchte man eine BĂŒhne, die durch ein GeradenstĂŒck reprĂ€sentiert ist, durch Lichtquellen, die durch Punkte in der Ebene reprĂ€sentiert sind, so beleuchten, dass jeder Punkt der BĂŒhne genĂŒgend Licht erhĂ€lt und dabei möglichst wenig Energie verbrauchen. Wenn man annimmt, dass die LichtintensitĂ€t stark mit der Entfernung zur Lichtquelle abnimmt, so stellt dies ein interesanntes geometrisches Optimierungsproblem dar. Wir geben verschiedene Lösungen an, die sowohl auf konvexer Optimierung, Diskretisierung und Linearer Programmierung basieren, als auch einen kombinatorischen Approximationsalgorithmus. Es werden auch experimentelle Resultate angegeben. Im zweiten Teil dieser Arbeit behandeln wir zwei verschiedene geometrische Probleme, deren Lösungen auf einer Datenstruktur basieren, die effiziente Anfragen beantworten kann. Die zentrale Idee unserer Datenstruktur ist die well-separated pair decomposition WSPD. Das erste Problem, das wir ansprechen ist das k-hop restricted shortest path under the power-euclidean distance function. FĂŒr n Punkte in der Ebene möchte man den kĂŒrzesten Pfad zwischen zwei beliebigen Punkten finden, der nicht mehr als k Kanten benötigt. Bekannte exakte Algorithmen fĂŒr dieses Problem benötigen W(nlogn) Zeit pro Anfrage (p;q). Wir lockern die Exaktheitsforderung und verlangen nur eine (1+e)-Approximation. Dies erlaubt uns eine Methode zu entwickeln, die konstante Zeit pro Anfrage garaniert und nur linearen Platz benötigt bei einer Vorverarbeitungszeit von O(nlogn). Die AbhĂ€ngigkeit von e ist polynomiell in 1=e. Außerdem entwickeln wir eine Methode, die davon unabhĂ€ngig von Interesse ist. FĂŒr ein Punktepaar p;q 2 P bestimmen wir in konstanter Zeit das Cluster-paar (A;B), das (p;q) in einer WSPD von P bestimmt. Das zweite Problem in diesem Teil ist das sogenannte cone-restricted nearest neighbor problem. FĂŒr eine gegebene Menge von Punkten im Euklidischen Raum betrachten wir das Problem den nĂ€chsten Nachbarpunkt zu bestimmen, der in einem Kegel liegt, dessen Spitze ein beliebiger Anfragepunkt ist. Wir untersuchen das dazugehörige Voronoi- Diagramm und entwickeln effiziente Datenstrukturen sowohl fĂŒr exakte als auch fĂŒr approximative cone-restricted nearest neighbor-Anfragen. Im speziellen entwickeln wir ein approximatives Voronoi-Diagramm der GrĂ¶ĂŸe O((n=ed) log(1=e)), das dazu benutzt werden kann, Anfragen in der Zeit O(log(n=e)) zu beantworten

    Geometric optimization and querying : exact & approximate

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    This thesis has two main parts. The first part deals with the stage illumination problem. Given a stage represented by a line segment L and a set of lightsources represented by a set of points S in the plane, assign powers to the lightsources such that every point on the stage receives a sufficient amount, e.g. one unit, of light while minimizing the overall power consumption. By assuming that the amount of light arriving from a fixed lightsource decreases rapidly with the distance from the lightsource, this becomes an interesting geometric optimization problem. We present different solutions, based on convex optimization, discretization and linear programming, as well as a purely combinatorial approximation algorithm. Some experimental results are also provided. In the second part of this thesis, we are concerned with two different geometric problems whose solutions are based on the construction of a data structure that would allow for efficient queries. The central idea of our data structures is the well-separated pair decomposition. The first problem we address is the k-hop restricted shortest path under the power-euclidean distance function. Given a set P of n points in the plane and the distance function jpqjd +Cp for some constant d > 1, nonnegative offset cost Cp and p;q 2 P, where jpqj denotes the Euclidean distance between p and q, we consider the problem of finding paths between any pair of points that minimize the lenght of the path and do not use more than some constant number k of hops. Known exact algorithms for this problem required W(nlogn) per query pair (p;q). We relax the exactness requirement and only require approximate (1+e) solutions which allows us to derive schemes which guarantee constant query time using linear space and O(nlogn) preprocessing time. The dependence on e is polynomial in 1=e. We also develop a tool that might be of independent interest: For any pair of points p;q 2 P report in constant time the cluster pair (A;B) representing (p;q) in a well-separated pair decomposition of P. The second problem in this part is so-called cone-restricted nearest neighbor. For a given point set in Euclidean space we consider the problem of finding (approximate) nearest neighbors of a query point but restricting only to points that lie within a fixed cone with apex at the query point. We investigate the structure of the Voronoi diagram induced by this notion of proximity and present approximate and exact data structures for answering cone-restricted nearest neighbor queries. In particular, we develop an approximate Voronoi diagram of size O((n=ed) log(1=e)) that can be used to answer cone-restricted nearest neighbor queries in O(log(n=e)) time.Diese Arbeit besteht aus zwei Teilen. Der erste Teil behandelt das Stage Illumination Problem. Hierbei möchte man eine BĂŒhne, die durch ein GeradenstĂŒck reprĂ€sentiert ist, durch Lichtquellen, die durch Punkte in der Ebene reprĂ€sentiert sind, so beleuchten, dass jeder Punkt der BĂŒhne genĂŒgend Licht erhĂ€lt und dabei möglichst wenig Energie verbrauchen. Wenn man annimmt, dass die LichtintensitĂ€t stark mit der Entfernung zur Lichtquelle abnimmt, so stellt dies ein interesanntes geometrisches Optimierungsproblem dar. Wir geben verschiedene Lösungen an, die sowohl auf konvexer Optimierung, Diskretisierung und Linearer Programmierung basieren, als auch einen kombinatorischen Approximationsalgorithmus. Es werden auch experimentelle Resultate angegeben. Im zweiten Teil dieser Arbeit behandeln wir zwei verschiedene geometrische Probleme, deren Lösungen auf einer Datenstruktur basieren, die effiziente Anfragen beantworten kann. Die zentrale Idee unserer Datenstruktur ist die well-separated pair decomposition WSPD. Das erste Problem, das wir ansprechen ist das k-hop restricted shortest path under the power-euclidean distance function. FĂŒr n Punkte in der Ebene möchte man den kĂŒrzesten Pfad zwischen zwei beliebigen Punkten finden, der nicht mehr als k Kanten benötigt. Bekannte exakte Algorithmen fĂŒr dieses Problem benötigen W(nlogn) Zeit pro Anfrage (p;q). Wir lockern die Exaktheitsforderung und verlangen nur eine (1+e)-Approximation. Dies erlaubt uns eine Methode zu entwickeln, die konstante Zeit pro Anfrage garaniert und nur linearen Platz benötigt bei einer Vorverarbeitungszeit von O(nlogn). Die AbhĂ€ngigkeit von e ist polynomiell in 1=e. Außerdem entwickeln wir eine Methode, die davon unabhĂ€ngig von Interesse ist. FĂŒr ein Punktepaar p;q 2 P bestimmen wir in konstanter Zeit das Cluster-paar (A;B), das (p;q) in einer WSPD von P bestimmt. Das zweite Problem in diesem Teil ist das sogenannte cone-restricted nearest neighbor problem. FĂŒr eine gegebene Menge von Punkten im Euklidischen Raum betrachten wir das Problem den nĂ€chsten Nachbarpunkt zu bestimmen, der in einem Kegel liegt, dessen Spitze ein beliebiger Anfragepunkt ist. Wir untersuchen das dazugehörige Voronoi- Diagramm und entwickeln effiziente Datenstrukturen sowohl fĂŒr exakte als auch fĂŒr approximative cone-restricted nearest neighbor-Anfragen. Im speziellen entwickeln wir ein approximatives Voronoi-Diagramm der GrĂ¶ĂŸe O((n=ed) log(1=e)), das dazu benutzt werden kann, Anfragen in der Zeit O(log(n=e)) zu beantworten

    Decomposing and packing polygons / Dania el-Khechen.

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    In this thesis, we study three different problems in the field of computational geometry: the partitioning of a simple polygon into two congruent components, the partitioning of squares and rectangles into equal area components while minimizing the perimeter of the cuts, and the packing of the maximum number of squares in an orthogonal polygon. To solve the first problem, we present three polynomial time algorithms which given a simple polygon P partitions it, if possible, into two congruent and possibly nonsimple components P 1 and P 2 : an O ( n 2 log n ) time algorithm for properly congruent components and an O ( n 3 ) time algorithm for mirror congruent components. In our analysis of the second problem, we experimentally find new bounds on the optimal partitions of squares and rectangles into equal area components. The visualization of the best determined solutions allows us to conjecture some characteristics of a class of optimal solutions. Finally, for the third problem, we present three linear time algorithms for packing the maximum number of unit squares in three subclasses of orthogonal polygons: the staircase polygons, the pyramids and Manhattan skyline polygons. We also study a special case of the problem where the given orthogonal polygon has vertices with integer coordinates and the squares to pack are (2 {604} 2) squares. We model the latter problem with a binary integer program and we develop a system that produces and visualizes optimal solutions. The observation of such solutions aided us in proving some characteristics of a class of optimal solutions

    Large bichromatic point sets admit empty monochromatic 4-gons

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    We consider a variation of a problem stated by Erd˝os and Szekeres in 1935 about the existence of a number fES(k) such that any set S of at least fES(k) points in general position in the plane has a subset of k points that are the vertices of a convex k-gon. In our setting the points of S are colored, and we say that a (not necessarily convex) spanned polygon is monochromatic if all its vertices have the same color. Moreover, a polygon is called empty if it does not contain any points of S in its interior. We show that any bichromatic set of n ≄ 5044 points in R2 in general position determines at least one empty, monochromatic quadrilateral (and thus linearly many).Postprint (published version

    16th Scandinavian Symposium and Workshops on Algorithm Theory: SWAT 2018, June 18-20, 2018, Malmö University, Malmö, Sweden

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    Resource Use in the Trinational Sangha River Region of Equatorial Africa: Histories, Knowledge Forms, and Institutions

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    This volume is based on an international conference, “Natural Resource Use Relations in the Trinational Sangha River Region of the Northwest Congo Basin,” held at Yale University in September 1997. In recognition of the bilingual context in which conservation occurs in the three countries of the Sangha region — Cameroon, Central African Republic, and Congo — all sessions of the conference were conducted simultaneously in French and English. This publication, which is a complete rendering of the conference papers and discussion sessions, is available in its entirety in both French and English
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