Nonlinear Programming: Theory and Algorithms | 
| Authors: Mokhtar S. Bazaraa, Hanif D. Sherali, C. M. Shetty
Publisher: Wiley-Interscience
Category: Book
List Price: $118.95
Buy New: $65.00
You Save: $53.95 (45%)
New (26) Used (10) from $54.52
Avg. Customer Rating:  3 reviews
Sales Rank: 119829
Media: Hardcover
Edition: 3
Number Of Items: 1
Pages: 872
Shipping Weight (lbs): 2.9
Dimensions (in): 9.4 x 6.2 x 1.8
ISBN: 0471486000
Dewey Decimal Number: 519.76
EAN: 9780471486008
ASIN: 0471486000
Publication Date: May 5, 2006
Availability: Usually ships in 1-2 business days
|
| Also Available In:
|
| Similar Items:
|
| Editorial Reviews:
Product Description
Nonlinear Programming: Theory and Algorithms-now in an extensively updated Third Edition- addresses the problem of optimizing an objective function in the presence of equality and inequality constraints. Many realistic problems cannot be adequately represented as a linear program owing to the nature of the nonlinearity of the objective function and/or the nonlinearity of any constraints. The Third Edition begins with a general introduction to nonlinear programming with illustrative examples and guidelines for model construction.
Important features of the Third Edition include:
* New topics such as second interior point methods, nonconvex optimization, nondifferentiable optimization, and more
* Updated discussion and new applications in each chapter
* Detailed numerical examples and graphical illustrations
* Essential coverage of modeling and formulating nonlinear programs
* Simple numerical problems
* Advanced theoretical exercises
The book is a solid reference for professionals as well as a useful text for students in the fields of operations research, management science, industrial engineering, applied mathematics, and also in engineering disciplines that deal with analytical optimization techniques. The logical and self-contained format uniquely covers nonlinear programming techniques with a great depth of information and an abundance of valuable examples and illustrations that showcase the most current advances in nonlinear problems.
|
| Customer Reviews:
Excellent Text October 7, 2008
This is a very good text for learning nonlinear programming. It expects that the reader has an understanding of linear algebra and mathematical sets but if you are prepared for a graduate NLP course then you'll find it accessible. It discusses how the problem formulation informs the type of algorithm best used to solve it as well as the algorithms themselves. As a graduate student, I highly recommend this book.
One of the best books on NLP at this level May 13, 2008
I am also referring to the 2nd Edition of the book.
I largely agree with review by Marc Sachon except the part about Dantzig's book: if you are new to LP/NLP, or Mathematical Programming in general, stay away from Dantzig's book. Its writing style is entirely outdated and will put you to sleep in no time. Reading from Dantzig to learn about LP is like reading Newton's originals to learn physics/calculus.
If you're new to LP / NLP I *strongly* recommend Vanderbei, and THEN this book.
This book covers enough ground for fast paced novices and beyond novices.
It's mathematical but not rigorous in the strict mathematician's way - for that kind of exposure look elsewhere. It covers a breadth of subjects/issues related to LP / NLP not often found in other books at its level, so in a way it is like a small compendium.
It's more up-to-date than say, R. Fletcher's "Practical Methods of Optimization", or Gill, Murray & Wright's "Practical Optimization" both good MSc level books but somewhat dated now and perhaps a bit tedious sometimes. However, if you're a novice, I advise you to look at them also, if you have access to them, as they might serve your specific needs/ reading style better/equally well. You should also look at Luenberger's "Linear and Nonlinear Programming" which is also quite old but has a classic writing style and is holding up rather well. If you want the fine nitty-gritty details and the breadth of coverage though, Bazaraa has more. Luenberger's more solid and rigorous.
Haven't had the chance to look at the more recent "Nonlinear Optimization" by Andrzej Ruszczynski but it might be as good/better as he's also an expert in the field - so keep that in mind.
"Convex Optimization" by Stephen Boyd is more advanced (not too advanced though, depending on your maths ability) and moving in a slightly different field/teritory.
Great Book for NLP (for the mathematically inclined only!) December 29, 1999
20 out of 22 found this review helpful
I am referring to the Bazaraa, Sherali and Shetty book "Nonlinear Programming, Theory and Applications", second edition (it seems that Amazon missed the third author).This is a great book for anyone who is interested in nonlinear optimization. The book presents the topic in a clear and concise manner, provides learning aides in form of examples and generally has a very well structured layout. I have other books on NLP, but I consider this the best one (Luenberger is great, too - but very condensed). The book consists of three parts: the first part presents convex analysis, the second part looks at optimality conditions and the third part presents algorithms. If you went through some OR textbooks and felt that they didn't give you enough on NLP, this is the place to get your fix! This book for NLPs together with Dantzig's work on LPs and you have the basic toolset for static optimization.
|
|
|
