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020 _a9780521195270
082 _a519.65
_bWIL
100 _aWilliamson, David P.
_916405
245 _aThe design of approximation algorithms
260 _bCambridge University Press
_aNew York
_c2011
300 _axi, 504 p.
365 _aGBP
_b58.99
520 _aDiscrete 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. Can be used as a textbook, but also as a way for students to get the background to read current research in the area of approximation algorithms Explores the heuristic solution of discrete optimization problems Explains the principles of designing approximation algorithms, around algorithmic ideas that have been used in different ways and applied to different optimization problems (https://www.cambridge.org/us/universitypress/subjects/computer-science/algorithmics-complexity-computer-algebra-and-computational-g/design-approximation-algorithms?format=HB&isbn=9780521195270)
650 _aApproximation theory
_916406
650 _aMathematical optimization
700 _aShmoys, David B.
_916407
942 _cBK
_2ddc
999 _c6651
_d6651