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## The Design of Approximation Algorithms (Hardback)"This book on approximation algorithms is a beautiful example of an ideal textbook. It gives a concise treatment of the major techniques, results, and references in approximation algorithms and provides an extensive and systematic coverage of this topic up to the frontier of current research. It will become a standard textbook and reference for graduate students, teachers, and researchers in the field." — Rolf H. Möhring, Technische Universität Berlin ## $33.25 |

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Please contact us if you've got questions about this product.## Condition

**LIKE NEW:** This book is in excellent, like-new condition.

## Description

From the back cover: “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 rival 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.”

**BRIEF CONTENTS**

- Preface
- I – An Introduction to the Techniques
- 1 – An Introduction to Approximation Algorithms
- 2 – Greedy Algorithms and Local Search
- 3 – Rounding Data and Dynamic Programming
- 4 – Deterministic Rounding of Linear Programs
- 5 – Random Sampling and Randomized Rounding of Linear Programs
- 6 – Randomized Rounding of Semidefinite Programs
- 7 – The Primal-Dual Method
- 8 – Cuts and Metrics
- II – Further Uses of the Techniques
- 9 – Further Uses of Greedy and Local Search Algorithms
- 10 – Further Uses of Rounding Data and Dynamic Programming
- 11 – Further Uses of Deterministic Rounding of Linear Programs
- 12 – Further Uses of Random Sampling and Randomized Rounding of Linear Programs
- 13 – Further Uses of Randomized Rounding of Semidefinite Programs
- 14 – Further Uses of the Primal-Dual Method
- 15 – Further Uses of Cuts and Metrics
- 16 – Techniques in Proving the Hardness of Approximation
- 17 – Open Problems
- Appendix A: Linear Programming
- Appendix B: NP-Completeness
- Bibliography
- Author Index
- Subject Index

## Details

- SKU:
- 1712
- Subject:
- Approximation Algorithms
- Author:
- Williamson, David P. and David B. Shmoys
- Publisher:
- Cambridge University Press
- Publish Date:
- 2011
- Format:
- Hardback
- Weight (pounds):
- 2.45
- Dimensions (W”xL”xH”):
- 7.3″x10.3″x1.3″
- ISBN-13:
- 9780521195270
- ISBN-10:
- 0521195276
- Grade Level:
- Graduate

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