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Network Flows: Theory, Algorithms, and Applications Hardcover – February 28, 1993

ISBN-13: 978-0136175490 ISBN-10: 013617549X Edition: 1st
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Editorial Reviews

From the Publisher

A comprehensive introduction to network flows that brings together the classic and the contemporary aspects of the field, and provides an integrative view of theory, algorithms, and applications.

From the Back Cover

Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications.

It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

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Product Details

  • Hardcover: 864 pages
  • Publisher: Prentice Hall; 1 edition (February 28, 1993)
  • Language: English
  • ISBN-10: 013617549X
  • ISBN-13: 978-0136175490
  • Product Dimensions: 7.3 x 1.9 x 9.3 inches
  • Shipping Weight: 4.4 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (14 customer reviews)
  • Amazon Best Sellers Rank: #420,060 in Books (See Top 100 in Books)

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Customer Reviews

4.6 out of 5 stars
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Most Helpful Customer Reviews

106 of 109 people found the following review helpful By A Customer on February 27, 2002
Format: Hardcover
First of all, I am not surprised that the book
got so many good reviews: at first look, it is truly
impressive, and it is clearly a work of love. I was
looking forward to teaching from it.
It is quite clear from the reviews though, that the
reviewers have not **used** it for teaching; they may
have browsed it at most.
The first disappointments came very soon in the course I
taught. The biggest flaw of the book is the really bad style
in which the proofs are written. They manage to be seemingly
overflowing with explanation, and at the same time difficult
to understand. They gloss over many details: if the teacher
tries to skip these, an alert student could easily make
him/her look pretty silly.
One case in point is the proof of the label correcting
algorithm's correctness starting on page 136. I knew this
material from before, so I thought preparing class from
here would be a breeze. I was wrong: after going back to
my notes, and breaking up the mess into several simple
claims did I manage to make notes from which I could teach.
Whoever missed the class was helpless, when they looked
for explanation in the book.
I only remark, that all classes that I taught from this book
were at some of the top 10 OR depts at the US... so this is
hardly the students' fault.
Many exercises are wrong as well, and although the authors
claim that they will try to fix the mistakes, they hardly ever
reply to reader's comments, as some of my fellow professors
told me.
I can only compare the style of the exposition to the
later written Combinatorial Optimization book by
Cunningham et. al. There is a WORLD of difference.
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16 of 16 people found the following review helpful By David W. Straight on December 17, 2004
Format: Hardcover
I've been using this book as the primary text for my class in

"Network Flow Programming" (senior & graduate level) at the

University of Tennessee for about 10 years. Prior to that time

I had used Jensen & Barnes' Network Flow Programming (now long out

of print). The code in Jensen & Barnes is in FORTRAN (not so fun

or useful for CS majors) and the intended audience seemed to be OR.

Ahuja's code is pascal pseudo-code for the most part, which usually

translates easily into the C language that most of our students

use.

For CS students, there is excellent use of algorithm analysis

(big-O) throughout the book, and there are long discussions

about different approaches and algorithms and the complexity of

each. There is a lot of mathematical notation, but my students

have never had to worry about PDEs and the like here. Any good

advanced CS student (graduate or undergraduate) will find the

book very worthwhile. In my course the students must implement

min-cost spanning trees, shortest paths, critical path/PERT

networks (not in Ahuja), max flow, and min-cost flow. I would

also recommend (for CS majors) Tarjan's excellent (and

succinct) Data Structures and Network Algorithms.
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24 of 28 people found the following review helpful By Dr. Lee D. Carlson HALL OF FAMEVINE VOICE on June 4, 2001
Format: Hardcover
This book is a comprehensive overview of network flow algorithms with emphasis on cost constraint algorithms. In chapter 1 the authors introduce the network flow problems that will be studied in the book along with a discussion of the applications of these problems.
The terminology needed for network flow problems is introduced in Chapter 2, with rigorous definitions given for graphs, trees, and network representations. Most interesting is the discussion on network transformations, for here the authors discuss how to simplify networks to make their study more tractable.
An overview of complexity concepts in algorithms is given in the next chapter. A good discussion is given on parameter balancing. Pseudocode is given at various places to illustrate the algorithms.
Chapter 4 discusses shortest-path algorithms, with emphasis on label-setting algorithms. For network modelers and designers involved in routing algorithms, there is a nice discussion of Dijkstra's algorithm in this chapter, along with a treatment of how to improve on that algorithm by using Dial's, heap, and radix heap implementations.
A more general discussion of shortest path algorithms follows in Chapter 5, with details on label-correcting algorithms. The reader is asked to investigate the Bellman's equations in the exercises.
The maximum flow algorithm is treated in Chapter 6, and the reader with a background in linear programming will see ideas from that area applied nicely here. An application to parallel programming is given also. The maximum flow problem is treated using algorithms that improve worst-case complexity in Chapter 7, by employing the preflow-push algorithms.
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1 of 1 people found the following review helpful By SMC on September 30, 2013
Format: Hardcover
I am an adjunct faculty member at a large university where I teach Network Optimization at the graduate level. In preparation for this course, I reviewed 10 textbooks on network optimization. This book was hands down the most informative and thorough text I reviewed. It was the clear winner in my analysis and I have been pleased with it for the past 3 years. I am impressed with how the authors incorporated so much theory and information into a single text yet took the time to add enough detail that one can, with a little thinking, pull the pieces together and easily understand the concepts. Each chapter includes:

1) Examples of how the algorithms are used. I have turned finding modern applications into an assignment for the students; they must find a recent journal article (within the last 5 years) that describes a new use of specific network algorithms (shortest path, minimum spanning tree, maxflow, min cost flow...).

2) Clearly developed, articulated, and frequently proven theorems, lemma's, and principals that explain why the algorithms achieve optimality (correctness and finiteness). This is the first textbook I have used as either a student or professor where understanding the proofs was a pleasurable experience

3) Clear development of computational complexity on most algorithms

4) Very good pseudocode for 80% of the algorithms in the text

5) A great selection of reference materials at the end of each chapter for further reseach

6) An excellent selection of practical and theoretical problems that reinforce the material presented in the chapter and stretch the student to understand the material and apply it to the next level.

Perhaps most important to me; the authors actually answer questions if you have them. Twice now, I have reached out to the authors and received timely information that went well beyond what I expected.
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