An Introduction to Optimization (Wiley-Interscience Series in Discrete Mathematics and Optimization) | 
| Authors: Edwin K. P. Chong, Stanislaw H. Zak
Publisher: Wiley-Interscience
Category: Book
List Price: $99.95
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Avg. Customer Rating:  6 reviews
Sales Rank: 849255
Media: Hardcover
Edition: 3
Number Of Items: 1
Pages: 608
Shipping Weight (lbs): 2.1
Dimensions (in): 9.3 x 6.2 x 1.4
ISBN: 0471758000
Dewey Decimal Number: 519.6
EAN: 9780471758006
ASIN: 0471758000
Publication Date: February 25, 2008
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Product Description
An Introduction to Optimization, Third Edition helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. The book is supplemented with numerous illustrations, an extensive bibliography, mathematical discussion at a level accessible to MBA and business students, a treatment of both linear and nonlinear programming, an introduction to recent developments such as neural networks and genetic algorithms, a chapter on the use of descent algorithms, and MATLAB exercises and examples.
Download Description
A modern, up-to-date introduction to optimization theory and methods
This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization.
Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked examples to illustrate both theory and algorithms, this book also provides:
* A review of the required mathematical background material
* A mathematical discussion at a level accessible to MBA and business students
* A treatment of both linear and nonlinear programming
* An introduction to recent developments, including neural networks, genetic algorithms, and interior-point methods
* A chapter on the use of descent algorithms for the training of feedforward neural networks
* Exercise problems after every chapter, many new to this edition
* MATLAB(r) exercises and examples
* Accompanying Instructor's Solutions Manual available on request
An Introduction to Optimization, Second Edition helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business.
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| Customer Reviews: Read 1 more reviews...
 Not for undergrads! May 8, 2008
I have a really difficult time with this book and often find myself having to do tons of outside research to comprehend the material. The sections are horribly short, genereally 2-3 pages which means there's no room for examples. Also, there are no answers in the back which leaves me wondering if I've screwed up somehow. This book really isn't meant for undergraduates. It's difficult to understand and too brief. It could use many more examples. If you've got a course in optimization, pray for a different book!
 It reads like source code April 18, 2007
2 out of 2 found this review helpful
I'm an undergraduate math major who is using this book in a linear programming course. The general consesus in my class is that this is a very difficult book to comprehend. Everything seems like it's been abstracted to the n-th degree. Variables are frequently used without reference to definitions, which in many cases appear in earlier sections. It's a pain to try to look up something then have to hunt around for the meaning of all the components used in the definition. That's not to say this book isn't informative, it just takes a lot of work to glean useful information from it. As a student, I prefer books that are easy to reference. I simply don't have time to read the whole chapter about the simplex method when I just want to know how to compute cost coefficients.
Rigor-Envy March 13, 2007
3 out of 3 found this review helpful
I can only speak on the linear programming section in this book. This is an awful text for undergraduates. This is a math text written by engineers who have a huge case of mathematical rigor-envy. They sacrifice all context, specificity, and practicality in lieu of a ridiculus level of mathematical generality. I am experienced in upper division proofing. I found myself reading and understanding every line of the proofs( of which there are many!) and still having no idea what had just been demonstrated. If you already have a PhD in pure mathematics, then this might be the book for you. If you are an undergraduate, stay away! If you need this book for a linear programming course, do youself a favor and also buy Linear Programming be Vasek Chvatal. The Chvatal text is the premier text on LP. It's only disadvantage is that it does not cover interior point methods, but this material can be easily supplemented from other sources. If yor are a prof. and are considering using this book for a undergraduate course, don't. Do your students some good and use a better text.
Not For Undergraduates April 23, 2004
3 out of 7 found this review helpful
This book should not be used to teach an Introduction to Optimization at the undergraduate level. It is being done so at my school, and it is driving the undergraduate students crazy because they do not understand the book, the notation also is causing problems. If you are new to the subject area, and do not have an advanced math background(more than college) try looking elsewhere.
 took the class, liked the book April 30, 1999
11 out of 13 found this review helpful
Drs. Chong and Zak are Professors of Electrical Engineering at Purdue, and Dr. Chong was the instructor for the ECE grad level optimization class when I took it spring '97. The book alone is good, detailed and rigorous enough for a graduate course without sacrificing readability or in-chapter examples. However, without the MATLAB examples that were developed by the authors to accompany lectures and illustrate each optimization method covered, the material might be a little abstract or dry for self-teaching. An excellent introduction or reference nonetheless, those without a solid base in linear algebra should keep a reference text handy while reading.
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