Titel: Approximation Algorithms
Autor/en: Vijay Vazirani
1. Auflage, 2. korr. Nachdruck 2003.
5. Dezember 2002 - gebunden - XX
Approximation algorithms are currently a central and fast-developing area of research in theoretical computer science. This monograph covers the basic techniques used in the latest research work, techniques that everyone in the field should know, and shows that they form the beginnings of a promising theory. The author consolidates progress made so far, including some very recent results, and makes a strong effort to convey the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, he writes algorithms in simple English to make them easy to understand, and he provides critical examples and numerous illustrations to help in elucidating the algorithms. Many of the results presented have been simplified and new insights provided. The book will interest theoretical computer scientists, operations researchers, and discrete mathematicians.
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.
From the reviews:
"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)
"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)
"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)
"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 a section 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)