Goberna, Miguel A.
Post-Optimal Analysis in Linear Semi-Infinite Optimization [electronic resource] / by Miguel A. Goberna, Marco A. López. - X, 121 p. 22 illus. in color. online resource. - SpringerBriefs in Optimization, 2190-8354 . - SpringerBriefs in Optimization, .
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.
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.
9781489980441
10.1007/978-1-4899-8044-1 doi
Mathematics.
Computer science.
Computer software.
Mathematics.
Operations Research, Management Science.
Models and Principles.
Programming Techniques.
Mathematical Software.
QA402-402.37 T57.6-57.97
519.6
Post-Optimal Analysis in Linear Semi-Infinite Optimization [electronic resource] / by Miguel A. Goberna, Marco A. López. - X, 121 p. 22 illus. in color. online resource. - SpringerBriefs in Optimization, 2190-8354 . - SpringerBriefs in Optimization, .
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.
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.
9781489980441
10.1007/978-1-4899-8044-1 doi
Mathematics.
Computer science.
Computer software.
Mathematics.
Operations Research, Management Science.
Models and Principles.
Programming Techniques.
Mathematical Software.
QA402-402.37 T57.6-57.97
519.6