Convex and Stochastic Optimization
Buch in deiner Nähe kaufen
Beschreibung
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.
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.
Provides a pedagogical, self-contained analysis of the theory of convex optimization and stochastic programming Offers a synthetical view of many applications such as semidefinite programming, Markov processes, generalized convexity and optimal transport Includes a study of algorithmic aspects: dynamic programming, stochastic dual dynamic programming (in the case of convex Bellman value functions) and linear decision rules
Autor*in
J. Frédéric Bonnans
Themen in »Convex and Stochastic Optimization«
Convex analysis Lagrangian duality Probability theory Semi-definite programming Stochastic programming Sample average approximation Dynamic optimization Risk measures Markov decision processes Numerical algorithms Optimal transport
Stimmen zu »Convex and Stochastic Optimization«
“The book is mainly devoted to the theoretical study of concepts of stochastic programming. … The book offers a solid theoretical background for researchers/students/practitioners keen on disposing of a rigorous foundation of stochastic programming.” (Wim van Ackooij, Mathematical Reviews, November, 2019)
()