Post-Optimal Analysis in Linear Semi-Infinite Optimization

✍ Scribed by Miguel A. Goberna, Marco A. López (auth.)

• Publisher: Springer-Verlag New York
• Year: 2014
• Tongue: English
• Leaves: 128
• Series: SpringerBriefs in Optimization
• Edition: 1
• Category: Library

✦ 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.

✦ Table of Contents

Front Matter....Pages i-x
Preliminaries on Linear Semi-infinite Optimization....Pages 1-22
Modeling Uncertain Linear Semi-infinite Optimization Problems....Pages 23-37
Robust Linear Semi-infinite Optimization....Pages 39-49
Sensitivity Analysis....Pages 51-60
Qualitative Stability Analysis....Pages 61-77
Quantitative Stability Analysis....Pages 79-107
Back Matter....Pages 109-121

✦ Subjects

Operations Research, Management Science; Models and Principles; Programming Techniques; Mathematical Software