The Design of Approximation Algorithms

Williamson, David P./ Shmoys, David B.

ISBN 10: 0521195276 / ISBN 13: 9780521195270

Published by Cambridge Univ Pr, 2011

About this Item

1st edition. 500 pages. 10.10x7.10x1.30 inches. In Stock. Seller Inventory # x-0521195276

Bibliographic Details

Title: The Design of Approximation Algorithms

Publisher: Cambridge Univ Pr

Publication Date: 2011

Binding: Hardcover

Condition: Brand New

About this title

Synopsis:

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.

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.