Download PDF Nonlinear Programming: Theory and Algorithms, by Mokhtar S. Bazaraa, C. M. Shetty
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Nonlinear Programming: Theory and Algorithms, by Mokhtar S. Bazaraa, C. M. Shetty
Download PDF Nonlinear Programming: Theory and Algorithms, by Mokhtar S. Bazaraa, C. M. Shetty
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A comprehensive, rigorous, and self-contained development of the central topics in nonlinear programming. Organized into three major sections: convex analysis, optimality conditions and duality, and algorithms and their convergence. Precise statements of the algorithms are given, along with convergence analysis. Among the topics covered are convex sets and functions, Fritz John and Kuhn Tucker optimality conditions, Lagrangian duality, Saddle Point optimality, constrained and unconstrained optimization, and the development of computational schemes. Includes extensive illustrations, examples, and references.
- Sales Rank: #4550807 in Books
- Published on: 1979-01-18
- Original language: English
- Number of items: 1
- Binding: Hardcover
- 560 pages
Most helpful customer reviews
8 of 8 people found the following review helpful.
One of the best books on NLP at this level
By S. Posantzis
I am also referring to the 2nd Edition of the book.
I largely agree with review by Marc Sachon except the part about Dantzig's book: if you are new to LP/NLP, or Mathematical Programming in general, stay away from Dantzig's book. Its writing style is entirely outdated and will put you to sleep in no time. Reading from Dantzig to learn about LP is like reading Newton's originals to learn physics/calculus.
If you're new to LP / NLP I *strongly* recommend Vanderbei, and THEN this book.
This book covers enough ground for fast paced novices and beyond novices.
It's mathematical but not rigorous in the strict mathematician's way - for that kind of exposure look elsewhere. It covers a breadth of subjects/issues related to LP / NLP not often found in other books at its level, so in a way it is like a small compendium.
It's more up-to-date than say, R. Fletcher's "Practical Methods of Optimization", or Gill, Murray & Wright's "Practical Optimization" both good MSc level books but somewhat dated now and perhaps a bit tedious sometimes. However, if you're a novice, I advise you to look at them also, if you have access to them, as they might serve your specific needs/ reading style better/equally well. You should also look at Luenberger's "Linear and Nonlinear Programming" which is also quite old but has a classic writing style and is holding up rather well. If you want the fine nitty-gritty details and the breadth of coverage though, Bazaraa has more. Luenberger's more solid and rigorous.
Haven't had the chance to look at the more recent "Nonlinear Optimization" by Andrzej Ruszczynski but it might be as good/better as he's also an expert in the field - so keep that in mind.
"Convex Optimization" by Stephen Boyd is more advanced (not too advanced though, depending on your maths ability) and moving in a slightly different field/teritory.
26 of 28 people found the following review helpful.
Great Book for NLP (for the mathematically inclined only!)
By Amazon Customer
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.
1 of 1 people found the following review helpful.
A very good book
By Flavio Cipparrone
This book presents the theory and algorithms of nonlinear programming.
Summaring the contents:
Ch1. Introduction
Part1 Convex Analysis
Ch2. Convex Sets
Ch3. Convex, PseudoConvex and QuasiConvex Functions
Part2 Optimality Conditions and Duality
Ch.4 The Fritz John and Karush-Kuhn-Tucker Optimality
Ch. 5 Constraint Qualifications
Ch. 6 Lagrangian Duality and Saddle Point Optimality Conditions
Part3 Algorithms and Their Convergence
Ch. 7 The Concept of an Algorithm (based on Zangwill work)
Ch. 8 Unconstrained Optimization (includes something about Trust Region)
Ch. 9 Penalty and Barrier Functions
Ch. 10 Methods of Feasible Directions
Ch. 11 Linear Complementary Problem, Quadratic, Separable, Fractional, and Geometric Programming
App. A Mathematical Review
App. B Summary of Convexity, Optimality Conditions, and Duality
-----------------------------
- Bu this edition as the second edition has several typos.
- a very good reference (up to date) for optimization courses.
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