Current courses

Past courses

  • Introduction a l'optimisation, École des Ponts Paristech, 1A, tronc commun
  • Optimisation et Energie, École des Ponts Paristech, 1A, cours d'ouverture
  • Recherche Opérationelle, École des Ponts Paristech, 2A
  • Introduction a l'optimisation stochastique, MPRO
  • Data Driven Robust Optimization, École des Ponts Paristech, 3A

Commented (slightly) and partial (very) bibliography

    Stochastic programming

  • Lectures on stochastic programming By A. Shapiro, D. Dentcheva and A. Ruszczynski.
    My reference book covering the theory of stochastic programming. For advanced users.
  • Introduction to stochastic programming J.Birge, F. Louveaux
    A very good book for OR students or user wanting to incorporate some stochasticity in their problems.
  • An optimization primer By J.Royset and R.Wets.
    A recent book, quite accessible, focusing on determinist and stochastic continuous optimization. It covers a wide array of tools from classical deterministic optimization, to stochastic programming and equilibrium problem.

    • Dynamic programming

  • Discrete-Time Markov Control Processes O. Hernandez-Lerma, J.B. Lasserre.
    An accessible, short, book dedicated to (discrete time) dynamic programming
  • Dynamic Programming and Optimal Control D. Bertsekas
    D. Bertsekas has written numerous optimization books, that are all reliable. This set of books might be the best for an introduction to discrete-time stochastic dynamic programming.
  • Reinforcement Learning R. Sutton A. Barto
    The reference book on reinforcement learning. Start with a chapter on dynamic programming.

    • Robust Optimization

  • Theory and Applications of Robust Optimization D. Bertsimas, D. Brown, C. Caramanis.
    This paper is the best introduction to robust optimization I have ever found.
  • A Practical Guide to Robust Optimization B. Gorissen, I. Yanikoglu, D. den Hertog.
    The title of this paper say all.

Various useful links