1 A convex optimization toolbox -- 2 Semidefinite and semi-infinite 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
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SUMMARY OR ABSTRACT
Text of Note
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
TOPICAL NAME USED AS SUBJECT
Entry Element
Mathematical optimization
Entry Element
Stochastic processes
Entry Element
Convex functions
a03
a05
a07
LIBRARY OF CONGRESS CLASSIFICATION
Class number
QA402
.
5
Book number
.
B66
2019
PERSONAL NAME - PRIMARY RESPONSIBILITY
Bonnans, J. F. (Joseph Frederic), 1957-
ORIGINATING SOURCE
Country
ایران
Agency
University of Tehran. Library of College of Science