Product Description
Addresses the problem of minimizing or maximizing a linear function in the presence of linear equality or inequality constraints. Provided are methods for modeling complex problems via effective algorithms on modern computers. The general theory and characteristics of optimization problems are presented, along with effective solution algorithms. Explores linear programming and network flows, employing polynomial-time algorithms and various specializations of the simplex method. Includes many numerical examples to illustrate theory and techniques.
 | US $31.57 End Date: Tuesday May-22-2012 15:12:36 PDT Buy It Now for only: US $31.57 Buy it now | Add to watch list |
I am having OR lesson in a university of Turkey.The problem is to solve the problems of this book.And it is very awful for me trying trying but even the results are not known.
Amazon User Rating: 3 / 5
I am using this book for a linear programming course. The most flagrant problem with this book is that it is filled with typos, making reading through proofs and examples very frustrating because you’re never sure what is supposed to be written. The book is also not very good at explaining concepts and leaves many steps out in the development of new ideas. If you can avoid it, do not use this book to learn linear programming.
Amazon User Rating: 2 / 5
I used this text while taking a graduate linear programming (LP)course on LP and network flows. I really liked the treatment. The typesetting was clear ,consistent and easily followed (not as good as Nash and Sofer’s). The book also includes lots of nice side discussion on how or why the theory is the way it is. Plenty of references are offered for further study. Proofs were not rigorous. The highly mathematical reader may be disappointed by the “show proof” style used instead of a rigorous theorem-proof style. In fact, I seem to recall a time or two where the theorem came after the usage. For me, I didn’t mind that, but a pure math guy would likely grind his teeth.
The network material was acceptable. I personally thought the text problems were not of the best quality. I would suggest a teacher supplement their own favorites outside of the book.
One caution is that the book is somewhat aged. I noticed a text like Nash and Sofer seems to have newer updates on the theory.
Overall, a great read for getting into the nitty gritty details of LP.
Amazon User Rating: 4 / 5
I used this book for 6 months and got nothing out of it. Ultimately I understood all the contents in 6 hours aften follwing a similar book by Puthenpura and Fang. However, this is very useful if you have a fairly good grasp of the subject and is useful for honing the skills.
Amazon User Rating: 2 / 5
I am currently working toward a Ph.D. in Management Science and used this book for a LP course. If you can get past the matrix algebra (which isn’t too terribly difficult) you will find that this book contains more practical LP information than any other resource available. However, those looking for a “how to” book on linear programming might want to try a more elementary text first. This book is geared toward those interested in the more advanced computational aspects of LP (e.g., revised simplex method, LU decomposition, product form of the inverse, bounded variables, etc.). The chapter on sensitivity analysis is particularly well written and thorough. But beware, this book packs more info per page than I have ever seen!!!
Amazon User Rating: 5 / 5