Post-Optimal Analysis in Linear Semi-Infinite Optimization

by Miguel A. Goberna, Marco A. López

Overview

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.

Product Details

ISBN-13:	9781489980434
Publisher:	Springer New York
Publication date:	01/07/2014
Series:	SpringerBriefs in Optimization
Edition description:	2014
Pages:	121
Product dimensions:	6.10(w) x 9.25(h) x 0.01(d)

Table of 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.