Rating:
(13 reviews)
Author: Ravindra K. Ahuja
ISBN : 013617549X
New from $104.00
Format: PDF
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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.
Direct download links available for Free Network Flows: Theory, Algorithms, and Applications [Hardcover]
- Hardcover: 864 pages
- Publisher: Prentice Hall; 1 edition (February 28, 1993)
- Language: English
- ISBN-10: 013617549X
- ISBN-13: 978-0136175490
- Product Dimensions: 1.8 x 7.2 x 9.4 inches
- Shipping Weight: 4.4 pounds (View shipping rates and policies)
Free Network Flows: Theory, Algorithms, and Applications
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.
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.