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An Introduction to Optimization, 2nd Edition
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
* 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.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
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
* 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.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
- GenresMathematics
496 pages, Hardcover
First published November 17, 1995
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Displaying 1 - 2 of 2 reviews
April 19, 2021
solid
A solid introduction. Good coverage of unconstrained optimization (linear, nonlinear), and constrained optimization (linear and nonlinear) - both over 'continuous' spaces. A solid focus on the centrality of Linear Programming (linear constrained optimization) and the still amazing Simplex Algorithm and the remarkable fact that though it is technically exponential in time in practice it seems to work out ok (polynomial time) in most cases. There is a good introduction to subsequent interior point algorithms for LP - Ellipsoidal and Karmarker. And a description of how these are 'almost' polynomial time. But they require floating point calculations of high precision - hundreds of digits for even small problems. Its kind of fascinating that you seem to be able to start moving from exponential time to polynomial time by moving from integers to reals. And of course reals can be only approximated - though sufficiently well for exact solutions to the original problem
My only criticism is the authors try a bit too hard. The notation is overly elaborate and more detailed than it needs to be. This is the symbolic correlate of 'too much jargon' in word space. Part One seems to be largely a waste of time. This is all covered much better elsewhere. Why repeat the obvious in a rushed way of no use at all to anyone who doesn't already know it.
A solid introduction. Good coverage of unconstrained optimization (linear, nonlinear), and constrained optimization (linear and nonlinear) - both over 'continuous' spaces. A solid focus on the centrality of Linear Programming (linear constrained optimization) and the still amazing Simplex Algorithm and the remarkable fact that though it is technically exponential in time in practice it seems to work out ok (polynomial time) in most cases. There is a good introduction to subsequent interior point algorithms for LP - Ellipsoidal and Karmarker. And a description of how these are 'almost' polynomial time. But they require floating point calculations of high precision - hundreds of digits for even small problems. Its kind of fascinating that you seem to be able to start moving from exponential time to polynomial time by moving from integers to reals. And of course reals can be only approximated - though sufficiently well for exact solutions to the original problem
My only criticism is the authors try a bit too hard. The notation is overly elaborate and more detailed than it needs to be. This is the symbolic correlate of 'too much jargon' in word space. Part One seems to be largely a waste of time. This is all covered much better elsewhere. Why repeat the obvious in a rushed way of no use at all to anyone who doesn't already know it.
January 2, 2023
I think the book needs more examples and some parts are very rushed, but the other parts are great. The exercises are pretty good though.
Displaying 1 - 2 of 2 reviews