Linear Programming: Foundations and Extensions

Author:   Robert J. Vanderbei
Publisher:   Springer-Verlag New York Inc.
Edition:   3rd ed. 2008
Volume:   v. 114
ISBN:  

9780387743875


Pages:   488
Publication Date:   26 November 2007
Replaced By:   9781461476290
Format:   Hardback
Availability:   Out of stock   Availability explained


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Linear Programming: Foundations and Extensions


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Overview

This Third Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with linear programming and then proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. You'll discover a host of practical business applications as well as non-business applications. With its focus on solving practical problems, the book features free C programs to implement the major algorithms covered. The book's accompanying website includes the C programs, JAVA tools, and new online instructional tools and exercises.

Full Product Details

Author:   Robert J. Vanderbei
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   3rd ed. 2008
Volume:   v. 114
Dimensions:   Width: 15.60cm , Height: 3.30cm , Length: 23.40cm
Weight:   0.977kg
ISBN:  

9780387743875


ISBN 10:   0387743871
Pages:   488
Publication Date:   26 November 2007
Audience:   College/higher education ,  Undergraduate
Replaced By:   9781461476290
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   Out of stock   Availability explained

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Reviews

From the reviews of the third edition: <p> Robert Vanderbeia (TM)s textbook on linear programming, now in its third edition, builds on many of the approaches used by ChvAtal and includes up-to-date coverage of a number of topics, including interior point methods, that have become important in the 25 years since the publication of ChvAtala (TM)s book. Vanderbeia (TM)s book is divided into four parts. a ] suitable for use in a first course in linear programming covering the simplex method at the advanced undergraduate or graduate level. (Brian Borchers, MathDL, May, 2008)


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