000 02394aam a2200349 a 4500
001 015663940
003 Uk
005 20181203101130.0
008 110114s2011 nyua b 001 0 eng
010 _a2011001945
015 _aGBB0B9301
_2bnb
016 7 _a015663940
_2Uk
020 _a9780521195270 (hbk.) :
_c£35.00
020 _a0521195276 (hbk.) :
_c£35.00
040 _aStDuBDS
_beng
_cStDuBDS
_dUk
042 _aukblsr
050 0 0 _aQA221
_b.W55 2011
082 0 0 _a518.5
_222
100 1 _aWilliamson, David P.
_923386
245 1 4 _aThe design of approximation algorithms
_cDavid P. Williamson, David B. Shmoys.
260 _aCambridge :
_bCambridge University Press,
_c2011.
300 _axi, 504 p. :
_bill. ;
_c26 cm.
500 _aFormerly CIP.
_5Uk
504 _aIncludes bibliographical references and indexes.
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.
_923387
650 0 _aMathematical optimization.
_923388
700 1 _aShmoys, David Bernard.
_923389
856 4 2 _3Cover image
_uhttp://assets.cambridge.org/97805211/95270/cover/9780521195270.jpg
942 _2ddc
_cBK
999 _c8580
_d8580