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Numerical Optimization (Anglais) Relié – 27 juillet 2006

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Numerical Optimization The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It is enhanced by new chapters on nonlinear interior methods and derivative-free methods for optimization. Full description

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Commentaires client les plus utiles sur (beta) 18 commentaires
26 internautes sur 33 ont trouvé ce commentaire utile 
Too much explanation, relative to the required background; some omissions in motivation 23 septembre 2006
Par Alexander C. Zorach - Publié sur
Format: Relié
While I acknowledge the many good points that the other reviewers pointed out, I found this book less than "optimal" in a number of respects.

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!
6 internautes sur 7 ont trouvé ce commentaire utile 
outstanding 15 mai 2007
Par kelly londry - Publié sur
Format: Relié Achat vérifié
This book is a well-written, outstanding reference for anyone interested in understanding, using, and/or implementing state-of-the-art techniques in nonlinear optimization. Ample attention is paid to both constrained and unconstrained problem types, with a healthy and refreshing emphasis on trust-region strategies, and modern SQP and Interior-Point algorithms. Sufficient detail is paid to most topics while overall perspectives are well-maintained. This book is the very best of its kind for its intended audience. I strongly recommend it.
5 internautes sur 6 ont trouvé ce commentaire utile 
The best book for engineers that want to implement too 3 octobre 2008
Par Amazon Customer - Publié sur
Format: Relié Achat vérifié
The book is quite complete and goes directly to the point. if you ever need optimization in your design you will find it here. Simple and well presented. It has enough details about algorithmic performance and description that should be enough to implement. It is a book that you will never regret having it in your library. If you want something more theoretical use Nonlinear Programming by Bertsekas. If you want to use optimization in your programs use this.
Essential scientific computing text 11 février 2015
Par Ben S. - Publié sur
Format: Relié
I'm a mechanical engineer by training, and computer vision scientist by experience. If you're into science/engineering and want to go the extra mile and do a little of your own scientific computation thing (you should, high demand niche. Temporarily sacrifice social life while you figure it out), I can't recommend this book enough.

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.
2 internautes sur 3 ont trouvé ce commentaire utile 
Optimal textbook 3 juin 2009
Par Z. Rafii - Publié sur
Format: Relié Achat vérifié
This textbook is kind of expensive (like many textbooks) but it is worthy. Everything about optimization is inside, well written and in details. And since everything is optimization, it can be really useful for all areas. I have just taken my final today in optimization with Nocedal as the instructor. He is as clear as his book, maybe more funny!
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