Approximation Algorithms for NP-hard Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Approximation Algorithms for NP-hard Problems write by Dorit S. Hochbaum. This book was released on 1997. Approximation Algorithms for NP-hard Problems available in PDF, EPUB and Kindle. This is the first book to fully address the study of approximation algorithms as a tool for coping with intractable problems. With chapters contributed by leading researchers in the field, this book introduces unifying techniques in the analysis of approximation algorithms. APPROXIMATION ALGORITHMS FOR NP-HARD PROBLEMS is intended for computer scientists and operations researchers interested in specific algorithm implementations, as well as design tools for algorithms. Among the techniques discussed: the use of linear programming, primal-dual techniques in worst-case analysis, semidefinite programming, computational geometry techniques, randomized algorithms, average-case analysis, probabilistically checkable proofs and inapproximability, and the Markov Chain Monte Carlo method. The text includes a variety of pedagogical features: definitions, exercises, open problems, glossary of problems, index, and notes on how best to use the book.
Approximation Algorithms
Approximation Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Approximation Algorithms write by Vijay V. Vazirani. This book was released on 2013-03-14. Approximation Algorithms available in PDF, EPUB and Kindle. Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.
Combinatorial Optimization -- Eureka, You Shrink!
Combinatorial Optimization -- Eureka, You Shrink! - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Combinatorial Optimization -- Eureka, You Shrink! write by Michael Jünger. This book was released on 2003-07-01. Combinatorial Optimization -- Eureka, You Shrink! available in PDF, EPUB and Kindle. This book is dedicated to Jack Edmonds in appreciation of his ground breaking work that laid the foundations for a broad variety of subsequent results achieved in combinatorial optimization.The main part consists of 13 revised full papers on current topics in combinatorial optimization, presented at Aussois 2001, the Fifth Aussois Workshop on Combinatorial Optimization, March 5-9, 2001, and dedicated to Jack Edmonds.Additional highlights in this book are an account of an Aussois 2001 special session dedicated to Jack Edmonds including a speech given by William R. Pulleyblank as well as newly typeset versions of three up-to-now hardly accessible classical papers:- Submodular Functions, Matroids, and Certain Polyhedranbsp;nbsp; by Jack Edmonds- Matching: A Well-Solved Class of Integer Linear Programsnbsp;nbsp; by Jack Edmonds and Ellis L. Johnson- Theoretical Improvements in Algorithmic Efficiency for Network Flow Problemsnbsp;nbsp; by Jack Edmonds and Richard M. Karp.
The Design of Approximation Algorithms
The Design of Approximation Algorithms - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Design of Approximation Algorithms write by David P. Williamson. This book was released on 2011-04-26. The Design of Approximation Algorithms available in PDF, EPUB and Kindle. Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing. Yet most such problems are NP-hard. Thus unless P = NP, there are no efficient algorithms to find optimal solutions to such problems. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first part of the book is devoted to a single algorithmic technique, which is then applied to several different problems. The second part revisits the techniques but offers more sophisticated treatments of them. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.
Algorithmics for Hard Problems
Algorithmics for Hard Problems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Algorithmics for Hard Problems write by Juraj Hromkovič. This book was released on 2013-03-14. Algorithmics for Hard Problems available in PDF, EPUB and Kindle. Algorithmic design, especially for hard problems, is more essential for success in solving them than any standard improvement of current computer tech nologies. Because of this, the design of algorithms for solving hard problems is the core of current algorithmic research from the theoretical point of view as well as from the practical point of view. There are many general text books on algorithmics, and several specialized books devoted to particular approaches such as local search, randomization, approximation algorithms, or heuristics. But there is no textbook that focuses on the design of algorithms for hard computing tasks, and that systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems. As this topic is fundamental for computer science, this book tries to close this gap. Another motivation, and probably the main reason for writing this book, is connected to education. The considered area has developed very dynami cally in recent years and the research on this topic discovered several profound results, new concepts, and new methods. Some of the achieved contributions are so fundamental that one can speak about paradigms which should be in cluded in the education of every computer science student. Unfortunately, this is very far from reality. This is because these paradigms are not sufficiently known in the computer science community, and so they are insufficiently com municated to students and practitioners.
