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Robust Optimization - (Princeton Applied Mathematics) by Aharon Ben-Tal & Laurent El Ghaoui & Arkadi Nemirovski (Hardcover)

Robust Optimization - (Princeton Applied Mathematics) by  Aharon Ben-Tal & Laurent El Ghaoui & Arkadi Nemirovski (Hardcover) - 1 of 1
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Highlights

  • Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology.
  • About the Author: Aharon Ben-Tal is professor of operations research at the Technion, Israel Institute for Technology.
  • 576 Pages
  • Business + Money Management, Operations Research
  • Series Name: Princeton Applied Mathematics

Description



Book Synopsis



Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject.

Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution.

The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations.

An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.



Review Quotes




"[T]his reference book gives an excellent and stimulating account of the classical and advanced results in the field, and should be consulted by all researchers and practitioners."---Joseph Frédéric Bonnans, Zentralblatt MATH

"Robust optimization is an active area of research that is likely to find many practical applications in the future. This book is an authoritative reference that will be very useful to researchers working in this area. Furthermore, the book has been structured so that the first part could easily be used as the text for a graduate level course in robust optimization."---Brian Borchers, MAA Reviews



About the Author



Aharon Ben-Tal is professor of operations research at the Technion, Israel Institute for Technology. Laurent El Ghaoui is associate professor of electrical engineering and operations research at the University of California, Berkeley. Arkadi Nemirovski is professor of industrial and systems engineering at Georgia Institute of Technology.
Dimensions (Overall): 10.0 Inches (H) x 7.2 Inches (W) x 1.4 Inches (D)
Weight: 2.9 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 576
Genre: Business + Money Management
Sub-Genre: Operations Research
Series Title: Princeton Applied Mathematics
Publisher: Princeton University Press
Format: Hardcover
Author: Aharon Ben-Tal & Laurent El Ghaoui & Arkadi Nemirovski
Language: English
Street Date: August 30, 2009
TCIN: 89022919
UPC: 9780691143682
Item Number (DPCI): 247-05-5578
Origin: Made in the USA or Imported
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Shipping details

Estimated ship dimensions: 1.4 inches length x 7.2 inches width x 10 inches height
Estimated ship weight: 2.9 pounds
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