The Design of Approximation Algorithms

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9780521195270: The Design of Approximation Algorithms

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.

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Book Description:

Designed as a textbook for graduate courses on algorithms, this book will also serve as a reference for researchers who are interested in heuristic solutions of discrete optimization problems. It presents central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization.

About the Author:

David P. Williamson is a Professor at Cornell University with a joint appointment in the School of Operations Research and Information Engineering and in the Department of Information Science. Prior to joining Cornell, he was a Research Staff Member at the IBM T. J. Watson Research Center and a Senior Manager at the IBM Almaden Research Center. He has won several awards for his work on approximation algorithms, including the 2000 Fulkerson Prize, sponsored by the American Mathematical Society and the Mathematical Programming Society. He has served on several editorial boards, including ACM Transactions on Algorithms, Mathematics of Operations Research, the SIAM Journal on Computing and the SIAM Journal on Discrete Mathematics.

David Shmoys has faculty appointments in both the School of Operations Research and Information Engineering and the Department of Computer Science, and he is currently Associate Director of the Institute for Computational Sustainability at Cornell University. He is a Fellow of the ACM, was an NSF Presidential Young Investigator, and has served on numerous editorial boards, including Mathematics of Operations Research (for which he is currently an associate editor), Operations Research, the ORSA Journal on Computing, Mathematical Programming and both the SIAM Journal on Computing and the SIAM Journal on Discrete Mathematics; he also served as editor-in-chief for the latter.

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David P. Williamson, David B. Shmoys
Editore: CAMBRIDGE UNIVERSITY PRESS, United Kingdom (2014)
ISBN 10: 0521195276 ISBN 13: 9780521195270
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Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2014. Hardback. Condizione libro: New. Language: English . Brand New Book. Discrete optimization problems are everywhere, from traditional operations research planning (scheduling, facility location and network design); to computer science databases; to advertising issues in viral marketing. Yet most such problems are NP-hard; unless P = NP, there are no efficient algorithms to find optimal solutions. 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 section is devoted to a single algorithmic technique applied to several different problems, with more sophisticated treatment in the second section. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithm courses, it will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems. Codice libro della libreria AAZ9780521195270

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David P. Williamson, David B. Shmoys
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Descrizione libro Cambridge University Press 2011-04-26, Cambridge, 2011. hardback. Condizione libro: New. Codice libro della libreria 9780521195270

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David P. Williamson, David B. Shmoys
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Descrizione libro CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2014. Hardback. Condizione libro: New. Language: English . Brand New Book. Discrete optimization problems are everywhere, from traditional operations research planning (scheduling, facility location and network design); to computer science databases; to advertising issues in viral marketing. Yet most such problems are NP-hard; unless P = NP, there are no efficient algorithms to find optimal solutions. 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 section is devoted to a single algorithmic technique applied to several different problems, with more sophisticated treatment in the second section. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithm courses, it will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems. Codice libro della libreria AAZ9780521195270

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Descrizione libro Cambridge University Press, 2011. Condizione libro: New. 2011. 1st Edition. Hardcover. Designed as a textbook for graduate courses on algorithms, this book presents efficient algorithms that find provably near-optimal solutions. Num Pages: 518 pages, 86 b/w illus. 121 exercises. BIC Classification: PBU; UMB; UMZ. Category: (U) Tertiary Education (US: College). Dimension: 256 x 186 x 32. Weight in Grams: 1154. 516 pages, 86 b/w illus. 121 exercises. Designed as a textbook for graduate courses on algorithms, this book presents efficient algorithms that find provably near-optimal solutions. Cateogry: (U) Tertiary Education (US: College). BIC Classification: PBU; UMB; UMZ. Dimension: 256 x 186 x 32. Weight: 1086. . . . . . . Codice libro della libreria V9780521195270

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Descrizione libro Cambridge University Press, 2011. HRD. Condizione libro: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Codice libro della libreria GB-9780521195270

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Descrizione libro Cambridge University Press. Condizione libro: New. 2011. 1st Edition. Hardcover. Designed as a textbook for graduate courses on algorithms, this book presents efficient algorithms that find provably near-optimal solutions. Num Pages: 518 pages, 86 b/w illus. 121 exercises. BIC Classification: PBU; UMB; UMZ. Category: (U) Tertiary Education (US: College). Dimension: 256 x 186 x 32. Weight in Grams: 1154. 516 pages, 86 b/w illus. 121 exercises. Designed as a textbook for graduate courses on algorithms, this book presents efficient algorithms that find provably near-optimal solutions. Cateogry: (U) Tertiary Education (US: College). BIC Classification: PBU; UMB; UMZ. Dimension: 256 x 186 x 32. Weight: 1086. . . . . . Books ship from the US and Ireland. Codice libro della libreria V9780521195270

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