Stochastic Multi-Stage Optimization

At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming

  • Pierre Carpentier
  • Jean-Philippe Chancelier
  • Guy Cohen
  • Michel De Lara
Part of the Probability Theory and Stochastic Modelling book series (PTSM, volume 75)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Preliminaries

    1. Front Matter
      Pages 1-1
    2. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 3-26
    3. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 27-62
  3. Decision Under Uncertainty and the Role of Information

    1. Front Matter
      Pages 63-63
    2. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 65-93
    3. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 95-132
    4. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 133-152
  4. Discretization and Numerical Methods

    1. Front Matter
      Pages 153-153
    2. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 155-180
    3. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 181-207
  5. Convergence Analysis

    1. Front Matter
      Pages 209-209
    2. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 211-252
  6. Multi-Agent Systems

    1. Front Matter
      Pages 253-253
    2. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 255-292
    3. Pierre Carpentier, Jean-Philippe Chancelier, Guy Cohen, Michel De Lara
      Pages 293-307
  7. Back Matter
    Pages 309-362

About this book

Introduction

The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.

Keywords

93C15, 93C39, 49-XX, 60-XX discretization dynamical information numerical approximation optimization stochastic optimal control stochastic programming

Authors and affiliations

  • Pierre Carpentier
    • 1
  • Jean-Philippe Chancelier
    • 2
  • Guy Cohen
    • 3
  • Michel De Lara
    • 4
  1. 1.ENSTA ParisTechPalaiseauFrance
  2. 2.Mathématiques et Calcul Scientifique (CERMICS)École Nationale des Ponts et Chaussées ParisTechMarne la ValléeFrance
  3. 3.CERMICSÉcole Nationale des Ponts et Chaussées ParisTechMarne la ValléeFrance
  4. 4.École Nationale des Ponts et Chaussées ParisTechMarne la ValléeFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18138-7
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-18137-0
  • Online ISBN 978-3-319-18138-7
  • Series Print ISSN 2199-3130
  • Series Online ISSN 2199-3149
  • About this book