<p>From the reviews:</p>
<p></p>
<p>"Approximation algorithms is an area where much progress has been made in the last 10 years. The book under review is a very good help for understanding these results. In each of the 27 chapters an important combinatorial optimization problem is presented and one or more approximation algorithms for it are clearly and concisely described and analyzed. In this way most of the most important results from the approximation algorithm literature are covered, often more easily comprehensible than the original articles." (Viggo Kann, Zentralblatt MATH, Vol. 1005, 2003)</p>
<p>"The book under review concentrates on the … design and analysis of efficient approximation algorithms with good performance guarantees. It is possibly the first textbook to provide an extensive and systematic coverage of this topic. … The book starts briskly, using simple examples to illustrate some of the key concepts and draw the reader rapidly in. … Copious exercises are included to test and deepen the reader’s understanding. … It deserves a place in every computer science and mathematical library." (Mark R. Jerrum, Mathematical Reviews, 2002 h)</p>
<p>"The book of Vijay Vazirani is not the first one dedicated to approximation algorithms … . However it is, I believe, among the very best from a didactical point of view: this is the text I would chose, would I have to give a course on approximation algorithms … . I suspect that for many researchers it would be the first one to consult … . It is a must acquisition for libraries of computer science/engineering departments … ." (Francesco Maffioli, Mathematical Methods of Operations Research, Vol. 56 (2), 2002)</p>
<p>"The book gives an overview on the theory of approximation algorithms. It presents the most important problems, the basic methods and ideas which are used in this area. … The book can be used for a graduate course on approximation algorithms. … The chapters also contain asection of exercises, which can help the students to understand the material in a deeper way. … On the other hand the book can be used by the researchers of the field … ." (Csanád Imreh, Acta Scientiarum Mathematicarum, Vol. 68, 2002)</p>

Although this may seem a paradox, all exact science is dominated by the idea of approximation. Bertrand Russell (1872-1970) Most natural optimization problems, including those arising in important application areas, are NP-hard. Therefore, under the widely believed con­ jecture that P -=/= NP, their exact solution is prohibitively time consuming. Charting the landscape of approximability of these problems, via polynomial time algorithms, therefore becomes a compelling subject of scientific inquiry in computer science and mathematics. This book presents the theory of ap­ proximation algorithms as it stands today. It is reasonable to expect the picture to change with time. This book is divided into three parts. In Part I we cover combinato­ rial algorithms for a number of important problems, using a wide variety of algorithm design techniques. The latter may give Part I a non-cohesive appearance. However, this is to be expected - nature is very rich, and we cannot expect a few tricks to help solve the diverse collection of NP-hard problems. Indeed, in this part, we have purposely refrained from tightly cat­ egorizing algorithmic techniques so as not to trivialize matters. Instead, we have attempted to capture, as accurately as possible, the individual character of each problem, and point out connections between problems and algorithms for solving them.
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In Part I we cover combinato­ rial algorithms for a number of important problems, using a wide variety of algorithm design techniques. Instead, we have attempted to capture, as accurately as possible, the individual character of each problem, and point out connections between problems and algorithms for solving them.
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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.
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 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

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Spreads powerful algorithmic ideas developed in this area to practitioners Will accelerate progress in this area Raises algorithmic awareness of the scientific community by showing simple ways of expressing complex algorithmic ideas An indispensable cookbook for all serious mathematical programmers Includes supplementary material: sn.pub/extras
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GPSR Compliance The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this. If you have any concerns about our products you can contact us on ProductSafety@springernature.com. In case Publisher is established outside the EU, the EU authorized representative is: Springer Nature Customer Service Center GmbH Europaplatz 3 69115 Heidelberg, Germany ProductSafety@springernature.com
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Produktdetaljer

ISBN
9783540653677
Publisert
2001-07-02
Utgiver
Vendor
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, UU, UP, P, 05, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

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