Convex and Stochastic Optimization

  • J. Frédéric Bonnans

Part of the Universitext book series (UTX)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. J. Frédéric Bonnans
    Pages 1-74
  3. J. Frédéric Bonnans
    Pages 75-116
  4. J. Frédéric Bonnans
    Pages 117-164
  5. J. Frédéric Bonnans
    Pages 165-176
  6. J. Frédéric Bonnans
    Pages 177-200
  7. J. Frédéric Bonnans
    Pages 201-222
  8. J. Frédéric Bonnans
    Pages 223-266
  9. J. Frédéric Bonnans
    Pages 267-281
  10. J. Frédéric Bonnans
    Pages 283-301
  11. Back Matter
    Pages 303-311

About this book


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.


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

Authors and affiliations

  • J. Frédéric Bonnans
    • 1
  1. 1.Inria and CMAPEcole PolytechniquePalaiseauFrance

Bibliographic information