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Item Details
Title:
ROBUST OPTIMIZATION
By:
Aharon Ben-Tal, Laurent El Ghaoui, Arkadi Nemirovski
Format:
Hardback
List price:
£88.00
Our price:
£70.40
Discount:
20
% off
You save:
£17.60
ISBN 10:
0691143684
ISBN 13:
9780691143682
Availability:
Usually dispatched within 3-5 days.
Delivery rates
Stock:
Currently
2
available
Publisher:
PRINCETON UNIVERSITY PRESS
Pub. date:
10 August, 2009
Series:
Princeton Series in Applied Mathematics
Pages:
576
Description:
Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.
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.
Illustrations:
36 line illus. 41 tables.
Publication:
US
Imprint:
Princeton University Press
Returns:
Returnable
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ADVANCES IN LINEAR MATRIX INEQUALITY METHODS IN CONTROL (PB)
LECTURES ON MODERN CONVEX OPTIMIZATION (PB)
LINEAR MATRIX INEQUALTIES IN SYSTEM AND CONTROL THEORY (PB)
OPTIMIZATION MODELS (HB)
ROBUST OPTIMIZATION
STATISTICAL INFERENCE VIA CONVEX OPTIMIZATION (HB)
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