Numerical Optimization

Rating:
Summary: Teaches good mathematical programming techniques
Review: The book does a very good job in teaching non-discrete mathematical programming techniques. But, it is not an introductory book. The reader is supposed to know linear algebra and numerical analysis to a certain extent. Most of the modern techniques are presented, but the layout is a little chaotic- the sequence of subjects could be made better. So, I would have preferred to give it 4.5 stars (which is impossible). However, that does not take away the fact that the book is excellent. I have used it primarily for modelling financial portfolios, and I am sure it can be used as a guide for other applications.

Conclusion: A little difficult, but well worth the time and money involved

Rating:
Summary: Nice but could be better!
Review: This book by Nocedal and Wright has several attractive features. For one, it is probably the most "state-of-the-art" of the existing texts in optimization and as such covers most of the modern methods. It also has a nice section on LP (simplex as well as interior point methods) for someone interested in a course on optimization as opposed to NONLINEAR optimization (which is what I was looking for). Another strength is that it covers many of the algebra-related details very well. My only major complaint is that it seems to not get into any of the methods designed specifically for convex programs - these while admittedly less general are often very powerful. For example, there is NO mention even of Geometric Programming which has wide application in design. The convex simplex method also isn't mentioned anywhere. Finally,I wonder why there is no mention of the generalized reduced gradient (GRG) method.

All in all, a good book to own I think...