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The Design of Approximation Algorithms (Relié)
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Résumé
Interesting 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 interesting discrete optimization 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. This book is organized around several 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 who are interested in the heuristic solution of discrete optimization problems.
This book shows how to design approximation algorithms : efficient algorithms that find provably near-optimal solutions. This book is organized around several 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 who are interested in the heuristic solution of discrete optimization problems.
Fiche technique
- Date de parution : 01/01/2011
- Editeur : Cambridge University Press
- ISBN : 978-0-521-19527-0
- EAN : 9780521195270
- Format : Grand Format
- Présentation : Relié
- Nb. de pages : 508 pages
- Poids : 1.16 Kg
- Dimensions : 18,8 cm × 26,4 cm × 3,3 cm
À propos des auteurs
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 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 currently an Associate Editor), Operations Research, ORSA Journal on Computing, Mathematical Programming, and the SIAM Journals of both Computing and Discrete Mathematics, where for the latter he also served as Editor-in-chief.
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 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 currently an Associate Editor), Operations Research, ORSA Journal on Computing, Mathematical Programming, and the SIAM Journals of both Computing and Discrete Mathematics, where for the latter he also served as Editor-in-chief.
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The Design of Approximation Algorithms
66,50 €