Optimization Under Uncertainty

Graduate course, MPRO, M2, 2023

This is a master level course about optimization under uncertainty, that take place at CNAM, (various room). See here for access information (“Matières” then “MPRO”).

Stochastic and Dynamic programming (by V. Leclère)

1. Stochastic Programming principles (13/11/24) 9:00 - 12:30

(St Martin : Accès 21 Etage 2 Salle 44) slides

  • Principles of optimization under uncertainties
  • Stochastic Programming approach, newsvendor problem
  • Information structure, VSS, EVPI
  • Sample Average Approximation

2. Robust Optimization principles (20/11/24) 9:00 - 12:30

(St Martin:Accès 17‑Etage 1‑Salle 04) slides

  • Robust optimization principles
  • Solving methodologies
  • The linear case
  • Probabilistic guarantees

3. Decomposition methods for two-stage stochastic programming (27/11/24) 9:00 - 12:30

(St Martin:Accès 17‑Etage 1‑Salle 04) slides

  • L-shaped decomposition
  • Progressive Hedging
  • Extension to multistage

4. Numerical methods for multistage stochastic programming (04/12/24) 9:00 - 12:30

(St Martin:Accès 21‑Etage 2‑Salle 28) slides

  • Heuristics: Model Predictive Control, (Repeated) Two-stage approximation
  • Dynamic Programming principle and extensions
  • SDDP algorithm for convex case

5. Numerical methods for robust optimization (11/12/24) 9:00 - 12:30

(St Martin:Accès 21‑Etage 2‑Salle 23) slides slides Risk-measures

  • Recourse model: affine decision rules, K-adaptability
  • Risk measures

6. Exam (18/12/23) 9:00 - 12:00

(St Martin:Accès 17‑Etage 2‑Salle 07)

Past exam (other course)

References