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Advances in Sensitivity Analysis and Parametric Programming (International Series in Operations Research & Management Science)

Advances in Sensitivity Analysis and Parametric Programming (International Series in Operations Research & Management Science)

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Creators: Tomas Gal, H.j. Greenberg
Publisher: Springer
Category: Book

List Price: $249.00
Buy New: $230.99
You Save: $18.01 (7%)



New (12) Used (8) from $203.52

Sales Rank: 3481612

Media: Hardcover
Edition: 1
Pages: 608
Number Of Items: 1
Shipping Weight (lbs): 2.3
Dimensions (in): 9.4 x 6.3 x 1.3

ISBN: 079239917X
Dewey Decimal Number: 519.7
EAN: 9780792399179

Publication Date: May 31, 1997
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: Brand new book! Delivered direct from our US warehouse by Expedited (4-7 days) or Standard (usually 10-14 days but can be longer). Expedited shipping recommended for speedier delivery. Over 1 million satisfied customers

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Product Description
The numerous advances in mathematical programming have opened up new insights about sensitivity analysis. The paradigm `What if...?' question is no longer the only question of interest. Often, we want to know `Why...?' and `Why not...?' Such questions were not analyzed in the early years of mathematical programming to the same extent that they are now, and we have not only expanded our thinking about `post-optimal analysis', but also about `solution analysis', even if the solution obtained is not optimal.
Therefore, it is now time to examine all the recent advances on sensitivity analysis and parametric programming. This book combines the origins of sensitivity analysis with the state of the art. It covers much of the traditional approaches with a modern perspective, and shows recent results using the optimal partition approach, stemming from interior methods, for both linear and quadratic programming. It examines the special case of network models. It presents a neglected topic, qualitative sensitivity analysis, as well as elements of mixed integer programming and gives a modern perspective of nonlinear programming. It provides recent advances in multi-criteria mathematical programming and also describes the state-of-the-art in stochastic programming. It covers recent advances in understanding redundancy in quadratic programs, considers an approach to diagnosing infeasibility in linear and nonlinear programs, and gives an overview of sensitivity analysis for fuzzy mathematical programming.


 
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