Goberna / López Post-Optimal Analysis in Linear Semi-Infinite Optimization

2014
ISBN: 978-1-4899-8044-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 121 Seiten, eBook

Reihe: SpringerBriefs in Optimization

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.

Zielgruppe

Research

Autoren/Hrsg.

Goberna, Miguel A.

López, Marco A.

Inhaltsverzeichnis

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.