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＜電子ブック＞
Convex and Stochastic Optimization / by J. Frédéric Bonnans
(Universitext. ISSN:21916675)

版	1st ed. 2019.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2019
本文言語	英語
大きさ	XIII, 311 p : online resource
著者標目	*Bonnans, J. Frédéric author SpringerLink (Online service)
件　名	LCSH:Mathematical optimization LCSH:Probabilities FREE:Optimization FREE:Probability Theory
一般注記	1 A convex optimization toolbox -- 2 Semidefinite and semiinfinite programming -- 3 An integration toolbox -- 4 Risk measures -- 5 Sampling and optimizing -- 6 Dynamic stochastic optimization -- 7 Markov decision processes -- 8 Algorithms -- 9 Generalized convexity and transportation theory -- References -- Index. This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting. It introduces and analyses the main algorithms for stochastic programs, while the theoretical aspects are carefully dealt with. The reader is shown how these tools can be applied to various fields, including approximation theory, semidefinite and second-order cone programming and linear decision rules. This textbook is recommended for students, engineers and researchers who are willing to take a rigorous approach to the mathematics involved in the application of duality theory to optimization with uncertainty HTTP:URL=https://doi.org/10.1007/978-3-030-14977-2

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