Convex Optimization and over one million other books are available for Amazon Kindle. Learn more
Buy New
$74.56
Qty:1
  • List Price: $95.00
  • Save: $20.44 (22%)
In Stock.
Ships from and sold by Amazon.com.
Gift-wrap available.
Convex Optimization has been added to your Cart
Trade in your item
Get a $33.90
Gift Card.
Have one to sell? Sell on Amazon
Flip to back Flip to front
Listen Playing... Paused   You're listening to a sample of the Audible audio edition.
Learn more
See all 2 images

Convex Optimization Hardcover – March 8, 2004

ISBN-13: 978-0521833783 ISBN-10: 0521833787

Buy New
Price: $74.56
39 New from $74.00 23 Used from $62.98
Amazon Price New from Used from
eTextbook
"Please retry"
Hardcover
"Please retry"
$74.56
$74.00 $62.98
Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student


Frequently Bought Together

Convex Optimization + The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
Price for both: $158.64

Buy the selected items together

NO_CONTENT_IN_FEATURE

Best Books of the Month
Best Books of the Month
Want to know our Editors' picks for the best books of the month? Browse Best Books of the Month, featuring our favorite new books in more than a dozen categories.

Product Details

  • Hardcover: 727 pages
  • Publisher: Cambridge University Press (March 8, 2004)
  • Language: English
  • ISBN-10: 0521833787
  • ISBN-13: 978-0521833783
  • Product Dimensions: 9.8 x 7.6 x 1.5 inches
  • Shipping Weight: 3.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (18 customer reviews)
  • Amazon Best Sellers Rank: #123,062 in Books (See Top 100 in Books)

Editorial Reviews

Review

"Boyd and Vandenberghe have written a beautiful book that I strongly recommend to everyone interested in optimization and computational mathematics: Convex Optimization is a very readable and inspiring introduction to this modern field of research...The book will be accessible not only to mathematicians but also to researchers and students who want to use convex optimization in applied fields like engineering, computer science, economics, statistics, or others. I recommend it as one of the best optimization textbooks that have appeared in the last years."
Mathematical Methods of Operations Research


"...this concisely writen book is useful in many regards: as a primary textbook for convex optimization with engineering applications or as an alternate text for a more traditional course on linear or nonlinear optimization."
Journal of the American Statistical Association, Hans-Jakob Luethi, Swiss Federal Institute of Technology Zurich


"The book by Boyd and Vandenberghe reviewed here is one of ... the best I have ever seen ... it is a gentle, but rigorous, introduction to the basic concepts and methods of the field ... this book is meant to be a 'first book' for the student or practitioner of optimization. However, I think that even the experienced researcher in the field has something to gain from reading this book: I have very much enjoyed the easy to follow presentation of many meaningful examples and suggestive interpretations meant to help the student's understanding penetrate beyond the surface of the formal description of the concepts and techniques. For teachers of convex optimization this book can be a gold mine of exercises."
MathSciNet

Book Description

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

4.5 out of 5 stars
5 star
14
4 star
1
3 star
2
2 star
0
1 star
1
See all 18 customer reviews
It is clearly written with a lot of examples.
Jerome Gilles
From an engineer's perspective I believe Boyd's book is much more easy to read and understand than Bertseka's book Convex Analysis and Optimization.
Amazon Customer
The authors have been very generous in allowing the free download of the full book from their website.
J. J. Arrieta-Camacho

Most Helpful Customer Reviews

33 of 35 people found the following review helpful By SP, ML, Stats on May 30, 2008
Format: Hardcover Verified Purchase
Quite simply, this is a wonderful text. Coupling this with Boyd's course at Stanford (the lecture videos, HWs, etc. are all available for free online), you're bound to learn quite a lot about optimization. But most importantly, you'll have an idea of when you can actually apply convex optimization to solve a problem that comes up in your particular field.

My reasoning in giving it such praise is my preference for the rather unusual methodology it takes in introducing you to optimization. Most books I have seen on linear programming or non-linear programming tackle a few standard problems, introduce what is necessary in terms of definitions and proofs, and then focus on the algorithms that solve these standard problems (conjugate gradient et. al.), how they work, their pitfalls, etc. While this is undoubtedly useful material (which Boyd does cover for a good deal in the final chapters), the simple fact of the matter is these algorithms are available as standard methods in optimization packages (which are abstracted from the user), and unless you are actually going into developing, implementing and tweaking algorithms, this quite honestly is useless.

What this book attempts to do, and does very well in my opinion, is to teach you to recognize convexity that's present in problems that are first glance appear to be so incredibly removed from optimization that you might never consider it. This book spends the first 100 pages or so just devoted to building a "calculus" of convexity, if you will, so that you know through what operations convexity is preserved, and you develop intuition as to the potential to use convex optimization in problems in your particular field or application.
Read more ›
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
24 of 25 people found the following review helpful By Amazon Customer on August 5, 2008
Format: Hardcover Verified Purchase
I think this is the best book for getting into optimization. It's simple with many examples and figures. Excellent choice for engineers, mathematicians might find it incomplete, but what can we do, that's life. I think the interior point section could have had more, but it is still ok. The next step after this book is Nemirovski's book "Lectures on Modern Convex optimization". You can download it for free from his website [...] along with many other notes. Nemirovski's book is very complete and has very modern ideas new to many engineers. But as I said Boyd's book is where you should start from. From an engineer's perspective I believe Boyd's book is much more easy to read and understand than Bertseka's book Convex Analysis and Optimization. I also appreciate Boyd's courtesy to have his book available on-line for free. I bought the book after downloading it because it is worth its price. Try also another book coming from Stanford, which is more specialized Convex Optimization & Euclidean Distance Geometry, also available on-line
2 Comments Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
24 of 27 people found the following review helpful By J. J. Arrieta-Camacho on March 2, 2006
Format: Hardcover
The book provides sound theoretical basis in a non-intimidating way. It also presents many examples that help the reader understand and relate his or her specific needs to general convex optimization problems. I think this book is a really good compromise between theory and practice: it can please the more mathematics-oriented with proofs, definitions, and bibliography; as well as the more application-oriented with examples, implementations, and heuristics. The authors have been very generous in allowing the free download of the full book from their website.
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
12 of 16 people found the following review helpful By Uttar on January 14, 2006
Format: Hardcover
The book excels in readability and style. A perfect balance on the theoretical and practical aspets of the convex optimization. As the name implies, and also as the authors put in preface, it is about recognizing, formulating, and solving convex optimization problems. Provides necessary mathematical background in the first part---not as deeply as a gradute level convex analysis book---and therefore helps reader build a working knowledge. If something is not covered in this part but essential for a working knowledge, then it is in the appendices for sure. Provides a wealth of examples, exercises, and applications. Perfect for self-study as well as classroom use.
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
21 of 29 people found the following review helpful By Math Reader on May 2, 2005
Format: Hardcover
This is an absolutely wonderful work on the subject. It delivers precisely what the preface promises -- a very comprehensive introduction to convex optimization for users. Moreover, it delivers far more, for it is incredibly well-written and unusually accessible. It's a joy to read.
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
1 of 1 people found the following review helpful By R Taylor on March 27, 2014
Format: Hardcover
I had the pdf of this book for years but was never able to really appreciate the book because this book is designed to be browsed.
Finally, I purchased a copy of the book (at a student bookstore) and just wanted to recommend it here.
Although the book would be considered an intermediate text, I believe the value of this book is that it contains a wealth of examples in terms of both theory and implementation.
Moreover, the examples show a lot of useful tricks that occur frequently in practical applications.
I cannot count the number of times I have found little gems in this book that were relevant to problems on which I had been working (the section on design of experiments is beautiful).
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again
1 of 1 people found the following review helpful By ralph kelsey on January 19, 2014
Format: Hardcover Verified Purchase
This material is somewhat tangential to my research, but I learned a ton by reading it. Very well organized.

For example, here is a problem I was working on. For a given matrix A, find vectors a and b such that

1. |A| <= ab^T, (outer product) and

2. a^Tb (inner product) is a minimum. Convex Optimization showed me how to convert this into a CO problem
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again

Most Recent Customer Reviews