Post-Optimal Analysis in Linear Semi-Infinite Optimization (Paperback, 2014)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	SpringerBriefs in Optimization
Release date:	2014
First published:	2014
Authors:	Miguel A. Goberna • Marco A. Lopez
Dimensions:	235 x 155 x 7mm (L x W x T)
Format:	Paperback
Pages:	121
Edition:	2014
ISBN-13:	978-1-4899-8043-4
Categories:	Books > Computing & IT > General theory of computing > General Books > Computing & IT > Computer programming > General Books > Computing & IT > Applications of computing > General Books > Business & Economics > Business & management > Management & management techniques > Operational research Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
LSN:	1-4899-8043-1
Barcode:	9781489980434

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