Terms and Conditions:
Robert J. Vanderbei wrote:NOTE: This pdf file is password protected against printing. Permission is not granted to print this document --- it is for online viewing only. Any attempt to print this pdf file is a violation of copyright law.
Linear Programming: Foundations and Extensions
is an introduction to the field of optimization. The book emphasizes constrained optimization
, beginning with a substantial treatment of linear programming
, and proceeding to convex analysis
, network flows
, integer programming
, quadratic programming
, and convex optimization
The book is carefully written. Specific examples and concrete algorithms precede more abstract topics. Topics are clearly developed with a large number of numerical examples worked out in detail.
Moreover, Linear Programming: Foundations and Extensions
underscores the purpose of optimization: to solve practical problems on a computer. Accordingly, the book is coordinated with free efficient C programs that implement the major algorithms studied :
- The two-phase simplex method;
- The primal-dual simplex method;
- The path-following interior-point method;
- The homogeneous self-dual methods.
In addition, there are online JAVA applets that illustrate various pivot rules and variants of the simplex method, both for linear programming and for network flows. These C programs and JAVA tools can be found on the book's webpage
. Also, check the book's webpage for new online instructional tools and exercises that have been added in the new edition.
, Operational Research
:) "The worked examples are excellent and very much to be welcomed. Resorting to clear examples to demonstrate the theory is usually deprecated - here it is done to great effect."
Robert M. Freund
:) "Overall, I greatly enjoyed reviewing this book, and I highly recommend the book as a textbook for an advanced undergraduate or master's level course in linear programming, particularly for courses in an engineering environment. In addition, the book also is a good reference book for interior point methods as well as for implementation and computational aspects of linear programming. This is an excellent new book."