- Amazon Student members save an additional 10% on Textbooks with promo code TEXTBOOK10. Enter code TEXTBOOK10 at checkout. Here's how (restrictions apply)
Numerical Optimization Hardcover – Jul 27 2006
Special Offers and Product Promotions
Frequently Bought Together
Customers Who Bought This Item Also Bought
No Kindle device required. Download one of the Free Kindle apps to start reading Kindle books on your smartphone, tablet, and computer.
To get the free app, enter your e-mail address or mobile phone number.
MMOR Mathematical Methods of Operations Research, 2001: "The books looks very suitable to be used in an graduate-level course in optimization for students in mathematics, operations research, engineering, and others. Moreover, it seems to be very helpful to do some self-studies in optimization, to complete own knowledge and can be a source of new ideas.... I recommend this excellent book to everyone who is interested in optimization problems."
From the Back Cover
Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.
For this new edition the book has been thoroughly updated throughout. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research. Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field. The authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.
Inside This Book(Learn More)
What Other Items Do Customers Buy After Viewing This Item?
Most Helpful Customer Reviews on Amazon.com (beta)
The text is very wordy and yet still sometimes lacks critical explanations. In particular, I found that the motivation for the ideas in earlier chapters is insufficient for the skeptical and questioning reader--one needs to put more trust in the author than I was comfortable with. The lines of reasoning used to motivate the methods are vague: Nocedal spends too much time talking about optimization from a distance. I would have appreciated a book that was more concise and that had more airtight reasoning, exploring questions more thoroughly.
I also feel that this book is impoverished with respect to algorithms. One does not encounter enough algorithms early on, and the book does not encourage enough experimentation. It also suffers from the very common "sin" among Numerical mathematics texts--it talks extensively about the convergence of algorithms before cultivating a deep understanding of those algorithms. The effect is that the reader gets bogged down with technical details. While the motivated reader can go off on her own and experiment to fill in these gaps and piece together the puzzle, I think most people who have this level of initiative and intellectual curiosity would be better served by a book that is more concise.
Following on this same theme, the level of explanation is not consistent with the level of background required to read the book. Some things are explained in a level of detail appropriate to an introductory undergraduate text, but the book requires substantial background in multivariable calculus and linear algebra. Someone without prior background in numerical linear algebra will probably find the notation in the book unintuitive and cumbersome; the appendices are of little help. But anyone with sufficient background to fully understand the material in this book will probably find it has too much explanation and moves too slowly.
I haven't found a better book on the topic yet; solving such an optimization problem seems to beyond the scope of the algorithms covered in this text. But I do feel confident that this book is not the best, due to the flaws I've mentioned above!
It goes over pretty much all the topics, and does so in a very practical manner while avoiding having raw code in the text (hate when authors do that). I especially love the treatment of the trust region method; everything you need to know is there, and the motivations are clear. It is very applied, as it should be given the nature of the topic, but remains mathematically rigorous throughout.
If you want a taste of what's there, search some of Nocedal's fine publications.
Look for similar items by category
- Books > Business & Investing > Management & Leadership > Operations Research
- Books > Professional & Technical > Business Management > Management & Leadership > Operations Research
- Books > Professional & Technical > Professional Science > Mathematics > Applied
- Books > Professional & Technical > Professional Science > Mathematics > Chaos & Systems
- Books > Professional & Technical > Professional Science > Mathematics > Number Systems
- Books > Professional & Technical > Professional Science > Mathematics > Pure Mathematics
- Books > Professional & Technical > Professional Science > Physics > System Theory
- Books > Qualifying Textbooks - Fall 2007 > Business & Investing
- Books > Qualifying Textbooks - Fall 2007 > Science
- Books > Science & Math > Mathematics > Applied > Linear Programming
- Books > Science & Math > Mathematics > Number Systems
- Books > Science & Math > Mathematics > Popular & Elementary > Counting & Numeration
- Books > Science & Math > Mathematics > Pure Mathematics > Calculus
- Books > Science & Math > Physics > Acoustics & Sound
- Books > Science & Math > Physics > Chaos & Systems
- Books > Science & Math > Physics > System Theory
- Books > Textbooks > Business & Finance
- Books > Textbooks > Sciences > Mathematics > Calculus