Post-Optimal Analysis in Linear Semi-Infinite Optimization (SpringerBriefs in Optimization)

✍ Scribed by Miguel Angel Goberna; Marco A. López

Publisher: Springer
Year: 2014
Tongue: English
Leaves: 128
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

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