Network Flows: Theory, Algorithms, and Applications

Missing first three chapters of the book to include the introduction chapter. Not very helpful for a class.

The best algorithm book ever!Really appreciate the reasoning the author gives, not just listing the algorithms like other books.Makes things simple and clear, in depth at the same time！

The tect can be hard to read and understand exactly what it is saying at times. Sometimes it took reading through the material before things would sink in and make sense.

Excellent! Item was delivered on time and as advertised.

As title shown, I was satisfied the service.It's just five days to get the book from I placed the order.Briefly, with modest price, it's quick and nice. Great job!

I've been using this book as the primary text for my class in"Network Flow Programming" (senior & graduate level) at theUniversity of Tennessee for about 10 years. Prior to that timeI had used Jensen & Barnes' Network Flow Programming (now long outof print). The code in Jensen & Barnes is in FORTRAN (not so funor useful for CS majors) and the intended audience seemed to be OR.Ahuja's code is pascal pseudo-code for the most part, which usuallytranslates easily into the C language that most of our studentsuse.For CS students, there is excellent use of algorithm analysis(big-O) throughout the book, and there are long discussionsabout different approaches and algorithms and the complexity ofeach. There is a lot of mathematical notation, but my studentshave never had to worry about PDEs and the like here. Any goodadvanced CS student (graduate or undergraduate) will find thebook very worthwhile. In my course the students must implementmin-cost spanning trees, shortest paths, critical path/PERTnetworks (not in Ahuja), max flow, and min-cost flow. I wouldalso recommend (for CS majors) Tarjan's excellent (andsuccinct) Data Structures and Network Algorithms.

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. Even more approaches to the maximum flow problem are considered in Chapter 8, where the reader can find a good presentation of dynamic tree implementations. All of the algorithms up to this point are put into the context of the minimum cost flow problem in Chapter 9. It is here that optimality conditions become very transparent in the implementation of the algorithms. A very quick but helpful discussion is given on sensitivity analysis of the minimum cost flow problem. An interesting application of the results is given to the problem of reconstructing the left ventricle in the heart from X-ray projections. Polynomial time algorithms for minimum cost flows are discussed effectively in Chapter 10, which is followed by a discussion of using linear programming methods in the minimum cost flow problem in Chapter 11. The application of combinatorial optimization techniques is the subject of Chapter 12, where matching problems are discussed. The authors give a thorough treatment, along with many examples. Spanning trees again make their appearance in Chapter 13, via the minimum spanning tree problem. The all-important Kruskal algorithm is given a detailed treatment, along with a very interesting discussion of matroids. Nonlinear optimization via convex cost flows is the subject of Chapter 14, wherein the authors show how to transform a convex cost flow problem into a minimum cost flow problem. Flow problems that are not conservative at the nodes are the subject of the next chapter on generalized flow problems. The solutions of these problems are discussed within the context of augmented forest structures, and many applications are given. Lagrangian methods are the subject of Chapter 16, where the authors show how to solve constrained shortest path algorithms using Lagrangian relaxation. It is here that one can see the interplay between all of the techniques introduced so far. Particularly interesting is the discussion on applications to the traveling salesman problem, vehicle routing, and network design.Flow problems where more than one entity are transferred across the network are the subject of Chapter 17, and logistic planners and engineers will find the treatment very helpful. Most helpful to those using network flow algorithms in their everyday work is the discussion in Chapter 18 on the computational testing of algorithms. The authors give a fine discussion on how to identify bottlenecks, compare performance differences between two algorithms, and how to use virtual running times instead of CPU times to test algorithms. The book ends with a chapter on more applications of network flow problems. Twenty-four applications are discussed, the most interesting ones to me being the optimal destruction of military targets, data scaling, DNA sequence alignment, automatic karyotyping of chromosomes, minimum project duration, just-in-time scheduling, warehouse layout, and inventory planning.

The content is very good and complete (4.5 stars of 5 ). You have very good reviews about content in amazon.com.The not so nice feature is that printing is not good. It seems it is a reprint using a photocopy as source. Letters are printed in gray (50%-70% black).

The book itself is very very good.It is well written and easy to understand.However, the printing quality is like reading a newspaper...

This book teaches you right from travelling Salesman problem to extremely advanced topics , heavy usage of big-o notation across the entire book.Paper quality must be improved, it's very bad. Shame on Pearson not improving the quality. It's not just about making money, but also grab readers attention, keep them engaged on the content of book , rather than quality of paper. Very disappointing. (This review should not affect the rating given)

I am very disappointed with this product. The book has many traces and marks. A corner of the cover has been hided with a black pen (one can read the text below:this edition is authorized for sale only in India). An absolute fraud.

Book in perfect conditions!