Customer Reviews

Optimization in Operations Research

5 star:		(16)
4 star:		(1)
3 star:		(0)
2 star:		(1)
1 star:		(0)

 

 

The "Search inside this book" feature was not available for this book when this review was published. Hope it helps.

Table of Contents
1. Problem Solving with Mathematical Models
2. Deterministic Optimization Models in Operations Research
3. Improving Search
4. Linear Programming Models
5. Simplex Search for Linear Programming
6. Interior Point Methods for Linear Programming
7. Duality and Sensitivity in Linear Programming
9. Shortest Path and Discrete Dynamic Programming
10. Network Flows
11. Discrete Optimization Models
12. Discrete Optimization Methods
13. Unconstrained Nonlinear Programming
14. Constrained Nonlinear Programming

If you need more information, Professor Rardin (Purdue University) maintains a website that can be easily located using any web search tool.

I thought there was only one best complete OR book is Hillier and Lieberman (H&L) until I got Rardin's book. Rardin presents the OR in different approach than H&L. The model building part is a little bit better than H&L, but the real meat is the fundamental of optimization. Search technique is well presented from the ground-up. This book can be served as the first book in OR if you're new to OR or the companion book if you know OR or even the first book in optimization in case you don't care to know OR.

I had absolutely no clue about optimization before I read this book. This book not only helped me overcome my diffidence, but also provided me with a very thorough understanding of the basics of the subject.

It is extremely difficult to criticize this book in any way. The language is plain English, not the technical jargon which other "introductory" books use. The book does not assume that the reader has a thorough understanding of linear algebra. Only a course in differential and integral calculus will do. The book provides several primers on a lot of topics- matrices, analysis, vectors etc., so that you do not have to interrupt your optimization studies and digress into these subjects.

There are three full chapters where the author provides real-life examples of mathematical modeling. Again, these are built up step-by-step, and not shoved down your throat.

The different approach to the Simplex Method is more intuitive than the traditional approach and more logical. The basic discussions on integer programming and non-linear programming are also worth mentioning. The numerous exercises and the presence of solutions to a number of them in the end make the text even more helpful.

The only somewhat weak point of the text is the chapter on interior point methods, where the book only provides the formulae and states that the derivations are "beyond the scope of the book". But, this is negligible and I recommend the book wholeheartedly

In my work I needed to find the shortest path from a single point to a set of points. This book really helped me to find the suitable method: the Dijkstra algorithm. I began reading Chapter 9, which is "Shortest Paths and Discrete Dynamic Programming". The material is presented clearly and with relevant and adequate variety of examples. I haven't read the other chapters since they are not required for my work at this moment and I don't have ample time to make a full review; however, I can say this: My many years in research in several fields have often put me in a position of transfering mathematical algorithms in one field to another or to search for an effecient one. I frequently get a limited time period to do literature search and I usually page-read many books. This is one of the rare books which are easy to read and comprehend. I thank and congratulate the author for doing a wonderful service.

As far as regards content, this is a fine book. It's a textbook, and it does that job.

I am commenting on the horrible cheap production: the publisher has effectively made a photocopy of the hardcover, and is selling it for $100. The cover is flimsy paper, scuffs and bends easily; the text on the pages is askew; and the contrast in the charts and shading is awful.

Review after 2 years of using this book: AMAZING BOOK. There has never been a better book (and probably never will be) in explaining OR.

Previous Review upon purchase:
If you are taking a graduate or an undergraduate course in OR, this book is a must! I have not seen ANY book able to present OR with such simple, direct examples and WITHOUT sacrificing theory.
This is the best written textbook I have ever read. When I compare it with the hundereds of dollars I spend on badly written books, even as a PG (poor graduate) student I would gladly pay twice of what this book is priced at.

Prof. Rardin's Optimization in OR is a great book. However the binding for the book does not do its justice as it is sold as a paperback at the Amazon.com. The binding of my copy quickly fell apart. With the kind of the price the book demands and its 900+pages size, it should be a hardback binding.

Rardin was the first book I used for OR and I keep a copy in my personal library. It offers a series of examples that are followed up throughout the book, chapter by chapter, to provide insight into the application of mathematics to real world problems. By building the level of complexity, on an ogoing basis through the use of specific examples, Rardin shows the extrmely practical side to why Operations Research is such a fundamental use of applied mathematics. The book is easy to read and should easily meet the needs of any upperlevel undergraduate course in Operations Research.

I got my B.S.E. in Industrial & OPS Eng. from U of Michigan. During that time, I had to take a course in Linear/Math. Programming. The course content was simple, but the book we used was TERRIBLE!!. Now finishing my M.S., I used this book in an OR class for my Masters Prog, and it is THE BEST BOOK! I literally read it page by page. It is the best written, hand holding book to a rather complicated subject. I got an A in the class, and gained great understanding. This is a book I WILL KEEP FOREVER, a great reference for the workplace as well!!!

This book presents the subjects in a different and novel way which provides many new insights.

In it, there is a great concern with the practical, professional use of operations research, as can be easily seen in the modeling examples. This book could be named "Optimization theory with realistic applications". This book certainly enables the students to apply the theory learned in practical situations, while providing the necessary mathematical foundations.

Rardin exposes the subject in a very clear and non-orthodox manner, unifying all algorithms through the use of the improving-search framework. The text is also innovative, containing sections on Genetic Algorithms, Simulated Annealing, Tabu Search and Branch and Cut.

But if you want to go deeper in some subject (linear programming for example) you will need another book.