Computational Geometry: Methods and Applications
by Jianer Chen
Number of pages: 227
In this book, we concentrate on four major directions in computational geometry: the construction of convex hulls, proximity problems, searching problems and intersection problems. Computational geometry is of practical importance because Euclidean space of two and three dimensions forms the arena in which real physical objects are arranged. A large number of applications areas such as pattern recognition, computer graphics, image processing, operations research, statistics, computer-aided design, robotics, etc., have been the incubation bed of the discipline since they provide inherently geo metric problems for which efficient algorithms have to be developed. A large number of manufacturing problems involve wire layout, facilities location, cutting-stock and related geometric optimization problems. Solving these efficiently on a high-speed computer requires the development of new geo metrical tools, as well as the application of fast-algorithm techniques, and is not simply a matter of translating well-known theorems into computer programs. From a theoretical standpoint, the complexity of geometric algo rithms is of interest because it sheds new light on the intrinsic difficulty of computation.
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by Wojciech Szpankowski - Wiley-Interscience
A book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms.
by Allen B. Downey - Green Tea Press
This book is intended for college students in computer science and related fields. The book also presents basic aspects of software engineering practice, including version control and unit testing. Each chapter ends with an exercises.
by Herbert Edelsbrunner - Duke University
The main topics to be covered in this course are: Design Techniques; Searching; Prioritizing; Graph Algorithms; Topological Algorithms; Geometric Algorithms; NP-completeness. The emphasis will be on algorithm design and on algorithm analysis.
by Sean Luke
This is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course.