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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Francisco J. Aragón (Ramón y Cajal Researcher), Miguel A. Goberna (Full Professor), Marco A. López (Full Professor), and Margarita M. L. Rodríguez (Associate Professor) are members of the Optimization Laboratory at the University of Alicante. Marco A. López is also Honorary Adjunct Professor of CIAO, Federation University, Ballarat (Australia). This group was created in the 1980s by the 2nd and 3rd authors, and works on the theory and methods for optimization problems. In particular, they have analyzed ordinary, semi-infinite, and infinite optimization problems from different perspectives (e.g., optimality, duality, stability, sensitivity and robustness), and have contributed with various numerical methods for linear and convex semi-infinite optimization problems and systems, together with new splitting algorithms for tackling feasibility and optimization problems. Miguel A. Goberna and Marco A. López are co-authors of the books Linear Semi-Infinite Optimization (J. Wiley, 1998) and Post-Optimal Analysis in Linear Semi-Infinite Optimization (SpringerBrief, 2014).
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 132 pp. Englisch. Bestandsnummer des Verkäufers 9781489980434
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