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Rating: 
Summary: Great Book for NLP (for the mathematically inclined only!)
Review: I am referring to the Bazaraa, Sherali and Shetty book "Nonlinear Programming, Theory and Applications", second edition (it seems that Amazon missed the third author).This is a great book for anyone who is interested in nonlinear optimization. The book presents the topic in a clear and concise manner, provides learning aides in form of examples and generally has a very well structured layout. I have other books on NLP, but I consider this the best one (Luenberger is great, too - but very condensed). The book consists of three parts: the first part presents convex analysis, the second part looks at optimality conditions and the third part presents algorithms. If you went through some OR textbooks and felt that they didn't give you enough on NLP, this is the place to get your fix! This book for NLPs together with Dantzig's work on LPs and you have the basic toolset for static optimization.
Rating:
Summary: Great Book for NLP (for the mathematically inclined only!)
Review: I am referring to the Bazaraa, Sherali and Shetty book "Nonlinear Programming, Theory and Applications", second edition (it seems that Amazon missed the third author). This is a great book for anyone who is interested in nonlinear optimization. The book presents the topic in a clear and concise manner, provides learning aides in form of examples and generally has a very well structured layout. I have other books on NLP, but I consider this the best one (Luenberger is great, too - but very condensed). The book consists of three parts: the first part presents convex analysis, the second part looks at optimality conditions and the third part presents algorithms. If you went through some OR textbooks and felt that they didn't give you enough on NLP, this is the place to get your fix! This book for NLPs together with Dantzig's work on LPs and you have the basic toolset for static optimization.
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