The book is an introductory textbook mainly for students of computer science and mathematics. It is an excellently written textbook designed to cater for a very wide-ranging readership. Its guiding phrase is "what every theoretical computer scientist should know about linear programming". A major focus is on applications of linear programming, both in practice and in theory. The book is concise, but at the same time, the main results are covered with complete proofs and in sufficient detail, ready for presentation in class.
The book does not require more prerequisites than basic linear algebra, which is summarized in an appendix. One of its main goals is to help the reader to see linear programming "behind the scenes".
Rezensionen / Stimmen
From the reviews:
"The authors' guiding phrase is 'what every theoretical computer scientist should know about linear programming'. . this book is easy and pleasant reading. A number of examples and illustrations are provided throughout the book. . The book is well written and well organized; I recommend it to undergraduate students and also to 'pure mathematicians' . . I recommend this book to computer scientists and mathematicians willing to learn the fundamentals of linear programming, and some of its many applications." (Fabio Mainardi, MAA Online, February, 2007)
"If you are looking for a concise and well-written overview of linear programming, then this may be the book for you. . The book is appropriate for nontheoretical computer scientists as well . . Matousek and Gärtner's Understanding and Using Linear Programming is a well-written introduction to the subject. . an excellent choice for anyone with a working knowledge of linear algebra who wants to learn more about the history and theory of linear programming, as it is written clearly and has a lively spirit." (Nancy C. Weida, SIAM Review, Vol. 49 (4), 2007)
"Focus in this interesting and recommendable textbook is on geometry and duality as well as on different solution algorithms for linear programming problems. The structure of the feasible set is explained and the relations between its vertices and basic feasible solutions are shown. . Both the ellipsoid and the interior point methods can be found in the textbook. The theory is complemented by many examples both from applications and relaxations of integer linear programming problems." (Stephan Dempe, Zentralblatt MATH, Vol. 1133 (11), 2008)
