000			01812cam a22002054a 4500
999			_c52283 _d52283
008			110114s2011 nyua b 001 0 eng
020			_a9780521195270 (Paperback)
041			_aeng
080			_a681.3 _bWIL
100	1		_aWilliamson David P
245	1	4	_aThe design of approximation algorithms
260			_aNew York _bCambridge University Press _c2011.
300			_axi, 504 Pages
520			_a"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"--
650		0	_aApproximation theory.
650		0	_aMathematical optimization.
690			_aComputer Science
700	1		_aShmoys, David Bernard
942			_cBK _02