---

＜電子ブック＞
Post-Optimal Analysis in Linear Semi-Infinite Optimization / by Miguel A. Goberna, Marco A. López
(SpringerBriefs in Optimization. ISSN:2191575X)

版	1st ed. 2014.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2014
本文言語	英語
大きさ	X, 121 p. 22 illus. in color : online resource
著者標目	*Goberna, Miguel A author López, Marco A author SpringerLink (Online service)
件　名	LCSH:Operations research LCSH:Management science LCSH:Computer science LCSH:Computer programming LCSH:Computer software FREE:Operations Research, Management Science FREE:Models of Computation FREE:Programming Techniques FREE:Mathematical Software
一般注記	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 HTTP:URL=https://doi.org/10.1007/978-1-4899-8044-1

 類似資料