Customer Reviews

Convex Optimization

5 star:		(9)
4 star:		(1)
3 star:		(1)
2 star:		(0)
1 star:		(1)

 

 

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. As such, the first part of the books is focused on building up the skill set, the second part to applications of convex programming, and only the third to the actual algorithms.

A word of warning: some of the explanations (especially in Chapter 4 which focuses on types of convex programs and equivalence of programs) are very general, which won't be satisfying to certain readers who need solid examples to reinforce the concepts. Also, a lot of the material can be quite challenging, requiring a bit of mental gymnastics. However, if you are accompanying your study with the problems at the end of each chapter, you're certain to get practice and demystify the concepts.

In sum, all things considered, a great text.

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.

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 http://www2.isye.gatech.edu/~nemirovs/ 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

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.

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.

This is an excellent text on optimization. The pdf version is free on the net. First I got the pdf version, I like the writing style and the way authors have described the concepts. Then I ordered the hard print. The print quality is excellent and its a great book to have!

Well written and intuitive. Check out the online copy by following the link from the convex programing page on Wikipedia.

This book trains you to recognize convexity, gives you the associated tools, also has a few chapters on the details of the tools. You will also end up knowing what to do when your problem is not convex. Coupled with Boyd's lecture videos and slides, it is an excellent place to learn about convex optimization for an engineer.

This book can be considered as a reference in convex optimization.
It is clearly written with a lot of examples.

Boyd's and Vanderbergue's book offers a lot: good intuition to theoretical convex optimization and its tools, sophisticated descriptions of many convex optimization applications, many examples and exercises. Combined with the online material of slides and videolectures by Boyd, exercise solutions, and matlab software, it is very well suited for classroom use, and an excellent starting point for the applications oriented reader.