Post-Optimal Analysis in Linear Semi-Infinite Optimization

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Synopsis

Post-Optimal Analysis in Linear Semi-Infinite Optimization examines the following topics in regards to linear semi-infinite optimization: modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis. Linear semi-infinite optimization (LSIO) deals with linear optimization problems where the dimension of the decision space or the number of constraints is infinite. The authors compare the post-optimal analysis with alternative approaches to uncertain LSIO problems and provide readers with criteria to choose the best way to model a given uncertain LSIO problem depending on the nature and quality of the data along with the available software. This work also contains open problems which readers will find intriguing a challenging. Post-Optimal Analysis in Linear Semi-Infinite Optimization is aimed toward researchers, graduate and post-graduate students of mathematics interested in optimization, parametric optimization and related topics.

Book details

Edition:
2014
Series:
SpringerBriefs in Optimization
Author:
Miguel A. Goberna, Marco A. López
ISBN:
9781489980441
Related ISBNs:
9781489980434
Publisher:
Springer New York
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-08-17
Usage restrictions:
Copyright
Copyright date:
2014
Copyright by:
Miguel A. Goberna, Marco A. López 
Adult content:
No
Language:
English
Categories:
Business and Finance, Computers and Internet, Mathematics and Statistics, Nonfiction