UID:
almahu_9948621593902882
Format:
XIX, 380 p.
,
online resource.
Edition:
1st ed. 2003.
ISBN:
9783662045657
Content:
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.
Note:
1 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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783642084690
Additional Edition:
Printed edition: ISBN 9783540653677
Additional Edition:
Printed edition: ISBN 9783662045664
Language:
English
DOI:
10.1007/978-3-662-04565-7
URL:
https://doi.org/10.1007/978-3-662-04565-7
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