000			03954nmm a22003375i 4500
005			20230705150648.0
008			130125s2003 gw | s |||| 0|eng d
020			_a9783662045657 _9978-3-662-04565-7
082			_a004.0151 _223
100			_aVazirani, Vijay V. _921057
245			_aApproximation Algorithms _h[electronic resource] / _cby Vijay V. Vazirani.
250			_a1st ed. 2003.
260			_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2003.
300			_aXIX, 380 p. _bonline resource.
505			_a1 Introduction -- I. Combinatorial Algorithms -- 2 Set Cover -- 3 Steiner Tree and TSP -- 4 Multiway Cut and k-Cut -- 5 k-Center -- 6 Feedback Vertex Set -- 7 Shortest Superstring -- 8 Knapsack -- 9 Bin Packing -- 10 Minimum Makespan Scheduling -- 11 Euclidean TSP -- II. LP-Based Algorithms -- 12 Introduction to LP-Duality -- 13 Set Cover via Dual Fitting -- 14 Rounding Applied to Set Cover -- 15 Set Cover via the Primal-Dual Schema -- 16 Maximum Satisfiability -- 17 Scheduling on Unrelated Parallel Machines -- 18 Multicut and Integer Multicommodity Flow in Trees -- 19 Multiway Cut -- 20 Multicut in General Graphs -- 21 Sparsest Cut -- 22 Steiner Forest -- 23 Steiner Network -- 24 Facility Location -- 25 k-Median -- 26 Semidefinite Programming -- III. Other Topics -- 27 Shortest Vector -- 28 Counting Problems -- 29 Hardness of Approximation -- 30 Open Problems -- A An Overview of Complexity Theory for the Algorithm Designer -- A.3.1 Approximation factor preserving reductions -- A.4 Randomized complexity classes -- A.5 Self-reducibility -- A.6 Notes -- B Basic Facts from Probability Theory -- B.1 Expectation and moments -- B.2 Deviations from the mean -- B.3 Basic distributions -- B.4 Notes -- References -- Problem Index.
520			_a This book covers the dominant theoretical approaches to the approximate solution of hard combinatorial optimization and enumeration problems. It contains elegant combinatorial theory, useful and interesting algorithms, and deep results about the intrinsic complexity of combinatorial problems. Its clarity of exposition and excellent selection of exercises will make it accessible and appealing to all those with a taste for mathematics and algorithms. Richard Karp,University Professor, University of California at Berkeley Following the development of basic combinatorial optimization techniques in the 1960s and 1970s, a main open question was to develop a theory of approximation algorithms. In the 1990s, parallel developments in techniques for designing approximation algorithms as well as methods for proving hardness of approximation results have led to a beautiful theory. The need to solve truly large instances of computationally hard problems, such as those arising from the Internet or the human genome project, has also increased interest in this theory. The field is currently very active, with the toolbox of approximation algorithm design techniques getting always richer. It is a pleasure to recommend Vijay Vazirani's well-written and comprehensive book on this important and timely topic. I am sure the reader will find it most useful both as an introduction to approximability as well as a reference to the many aspects of approximation algorithms. László Lovász, Senior Researcher, Microsoft Research.
650			_aComputer science. _921058
650			_aAlgorithms. _921059
650			_aComputer science-Mathematics. _921060
650			_aDiscrete mathematics. _921061
650			_aOperations research. _921062
650			_aNumerical analysis. _921063
650			_aTheory of Computation. _921064
650			_aAlgorithms. _921059
650			_aDiscrete Mathematics in Computer Science. _921065
650			_aOperations Research and Decision Theory. _921066
650			_aDiscrete Mathematics. _921067
650			_aNumerical Analysis. _921068
856			_uhttps://doi.org/10.1007/978-3-662-04565-7
942			_cEBK
999			_c13712 _d13712