Post-Optimal Analysis in Linear Semi-Infinite Optimization / SpringerBriefs in Optimization (PDF)
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- Autoren: Miguel A. Goberna , Marco A. López
- 2014, 2014, 121 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 148998044X
- ISBN-13: 9781489980441
- Erscheinungsdatum: 06.01.2014
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Grösse: 2 MB
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Englisch
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