Approximation Algorithms / Edition 1

Approximation Algorithms / Edition 1

by Vijay V. Vazirani
ISBN-10:
3540653678
ISBN-13:
2903540653676
Pub. Date:
08/09/2001
Publisher:
Approximation Algorithms / Edition 1

Approximation Algorithms / Edition 1

by Vijay V. Vazirani
$62.59
Current price is , Original price is $99.99. You
$99.99 
  • SHIP THIS ITEM
    In stock. Ships in 1-2 days.
  • PICK UP IN STORE

    Your local store may have stock of this item.

  • SHIP THIS ITEM

    Temporarily Out of Stock Online

    Please check back later for updated availability.


Overview

This monograph deals with designing polynomial time approximation algorithms for NP-hard combinatorial optimization problems. Although NP-complete problems do not offer footholds to find optimal solutions efficiently, they offer footholds to find near-optimal solutions efficiently. Designing polynomial time algorithms involves finding these footholds and exploiting them. The book discusses a wide range of combinatorial and LP-based algorithms in detail.

Product Details

ISBN-13: 2903540653676
Publication date: 08/09/2001
Edition description: 1st ed. 2001. Corr. 2nd printing 2002
Pages: 380
Product dimensions: 6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

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.

What People are Saying About This

Laszlo Lovasz

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.
Senior Researcher, Microsoft Research

Richard Karp

"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.
University of California at Berkeley

From the B&N Reads Blog

Customer Reviews