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Mathematics - Applications | Post-Optimal Analysis in Linear Semi-Infinite Optimization

Post-Optimal Analysis in Linear Semi-Infinite Optimization

Goberna, Miguel A., López, Marco A.

2014, X, 121 p. 22 illus. in color.

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  • Depicts modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis in relation to linear semi-infinite optimization
  • Emphasizes main concepts, results and technical aspects of linear semi-infinite optimization to readers in various fields
  • Contains recent results on the emerging quantitative stability and sensitivity theories
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.

Content Level » Research

Keywords » Linear optimization - Parametric optimization - Semi-infinite optimization - Sensitivity analysis - Stability analysis - Uncertain optimization

Related subjects » Applications - Computational Science & Engineering - Information Systems and Applications - Software Engineering

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.

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