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OverviewDiscrete 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. Full Product DetailsAuthor: David P Williamson (Cornell University, New York) , David B Shmoys (Cornell University, New York)Publisher: Cambridge University Press Imprint: Cambridge University Press ISBN: 9786613110961ISBN 10: 6613110965 Pages: 518 Publication Date: 26 April 2011 Audience: General/trade , General Format: Electronic book text Publisher's Status: Active Availability: Out of stock  The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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