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Robust Optimization /

Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of r...

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Detalles Bibliográficos
Autor principal: Ben-Tal, A.
Otros Autores: Nemirovskiĭ, A. S. (Arkadiĭ Semenovich), El Ghaoui, Laurent
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Princeton : Princeton University Press, 2009.
Colección:Book collections on Project MUSE.
Temas:
Acceso en línea:Texto completo

MARC

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245 1 0 |a Robust Optimization /   |c Aharon Ben-Tal, Laurent El Ghaoui, Arkadi Nemirovski. 
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490 0 |a Princeton series in applied mathematics 
505 0 |a pt. I. Robust Linear Optimization -- Ch. 1. Uncertain Linear Optimization Problems and their Robust Counterparts -- Ch. 2. Robust Counterpart Approximations of Scalar Chance Constraints -- Ch. 3. Globalized Robust Counterparts of Uncertain LO Problems -- Ch. 4. More on Safe Tractable Approximations of Scalar Chance Constraints -- pt. II. Robust Conic Optimization -- Ch. 5. Uncertain Conic Optimization: The Concepts -- Ch. 6. Uncertain Conic Quadratic Problems with Tractable RCs -- Ch. 7. Approximating RCs of Uncertain Conic Quadratic Problems -- Ch. 8. Uncertain Semidefinite Problems with Tractable RCs -- Ch. 9. Approximating RCs of Uncertain Semidefinite Problems -- Ch. 10. Approximating Chance Constrained CQIs and LMIs -- Ch. 11. Globalized Robust Counterparts of Uncertain Conic Problems -- Ch. 12. Robust Classification and Estimation -- pt. III. Robust Multi-Stage Optimization -- Ch. 13. Robust Markov Decision Processes -- Ch. 14. Robust Adjustable Multistage Optimization -- pt. IV. Selected Applications -- Ch. 15. Selected Applications -- App. A. Notation and Prerequisites -- App. B. Some Auxiliary Proofs -- App. C. Solutions to Selected Exercises -- Index. 
520 |a Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to opera. 
546 |a In English. 
588 |a Description based on print version record. 
650 7 |a Robust optimization.  |2 fast  |0 (OCoLC)fst01740908 
650 7 |a Linear programming.  |2 fast  |0 (OCoLC)fst00999090 
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650 7 |a MATHEMATICS  |x Optimization.  |2 bisacsh 
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650 6 |a Optimisation robuste. 
650 0 |a Linear programming. 
650 0 |a Robust optimization. 
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700 1 |a Nemirovskiĭ, A. S.  |q (Arkadiĭ Semenovich) 
700 1 |a El Ghaoui, Laurent. 
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