Modern Birkhäuser Classics

Linear Programming

Authors: Karloff, Howard

  • An affordable new softcover edition of a classic text
  • A survey of linear programming accessible to upper-division undergraduate and graduate students
  • A self-contained, concise mathematical introduction to the theory of linear programming
  • Replete with exercises and illustrations
  • The exposition is clear and elementary; the style is informal without sacrificing anything necessary for understanding
  • Contains both theory and computational practice
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Buy this book

eBook $39.99
price for USA (gross)
  • ISBN 978-0-8176-4844-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $49.99
price for USA
  • ISBN 978-0-8176-4843-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study.

—Choice Reviews

 

The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming.

—Mathematics of Computing

 

This is a textbook intended for advanced undergraduate or graduate students. It contains both theory and computational practice. After preliminary discussion of linear algebra and geometry, it describes the simplex algorithm, duality, the ellipsoid algorithm (Khachiyan’s algorithm) and Karmarkar’s algorithm.

—Zentralblatt Math

 

The exposition is clear and elementary; it also contains many exercises and illustrations.

—Mathematical Reviews

 

A self-contained, concise mathematical introduction to the theory of linear programming.

—Journal of Economic Literature

Reviews

From the reviews:

“… the reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming.” (Mathematics of Computing)

“The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful. … Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study.” (Choice Reviews)


Table of contents (5 chapters)

Buy this book

eBook $39.99
price for USA (gross)
  • ISBN 978-0-8176-4844-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $49.99
price for USA
  • ISBN 978-0-8176-4843-5
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Linear Programming
Authors
Series Title
Modern Birkhäuser Classics
Copyright
1991
Publisher
Birkhäuser Basel
Copyright Holder
Birkhäuser Boston
eBook ISBN
978-0-8176-4844-2
DOI
10.1007/978-0-8176-4844-2
Softcover ISBN
978-0-8176-4843-5
Series ISSN
2197-1803
Edition Number
1
Number of Pages
VIII, 144
Number of Illustrations and Tables
6 b/w illustrations
Additional Information
Originally published in the series: Progress in Theoretical Computer Science
Topics