Post-Optimal Analysis in Linear Semi-Infinite Optimization

By Miguel Angel Goberna and Marco A. López

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.

• Format: Paperback
• Language: English
• ISBN: 1489980431
• ISBN13: 9781489980434
• Release Date: January 2014
• Publisher: Springer
• Length: 121 Pages
• Weight: 0.43 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"