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Post-Optimal Analysis in Linear Semi-Infinite Optimization [electronic resource] / by Miguel A. Goberna, Marco A. López.

By: Goberna, Miguel A [author.].
Contributor(s): López, Marco A [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Optimization: Publisher: New York, NY : Springer New York : Imprint: Springer, 2014Description: X, 121 p. 22 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781489980441.Subject(s): Mathematics | Computer science | Computer software | Mathematics | Operations Research, Management Science | Models and Principles | Programming Techniques | Mathematical SoftwareDDC classification: 519.6 Online resources: Click here to access online
Contents:
1. Preliminaries on Linear Semi-Infinite Optimization -- 2. Modeling uncertain Linear Semi-Infinite Optimization problems -- 3. Robust Linear Semi-infinite Optimization -- 4. Sensitivity analysis -- 5. Qualitative stability analysis -- 6. Quantitative stability analysis.
In: Springer eBooksSummary: 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.
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1. Preliminaries on Linear Semi-Infinite Optimization -- 2. Modeling uncertain Linear Semi-Infinite Optimization problems -- 3. Robust Linear Semi-infinite Optimization -- 4. Sensitivity analysis -- 5. Qualitative stability analysis -- 6. Quantitative stability analysis.

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.

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