Optimization Under Uncertainty
Graduate course, MPRO, M2, 2026
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 (04/11/26) 9:00 - 12:30
- Principles of optimization under uncertainties
- Stochastic Programming approach, newsvendor problem
- Information structure, VSS, EVPI
- Sample Average Approximation
2. Robust Optimization principles (25/11/26) 9:00 - 12:30
(St Martin : Accès 21 - Etage 2 - Salle 37) slides
- Robust optimization principles
- Solving methodologies
- The linear case
- Probabilistic guarantees
3. Decomposition methods for two-stage stochastic programming (02/12/26) 9:00 - 12:30
(St Martin : Accès 21 - Etage 2 - Salle 20) slides
- L-shaped decomposition
- Progressive Hedging
- Extension to multistage
4. Numerical methods for multistage stochastic programming (09/12/26) 9:00 - 12:30
(St Martin : Accès 17 - Etage 1 - Salle 04) 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 (16/12/26) 9:00 - 12:30
(Conté : Accès 30 - Sous-sol - Salle 21) slides slides Risk-measures
- Recourse model: affine decision rules, K-adaptability
- Risk measures
6. Exam (06/01/27) 9:00 - 12:00
(St Martin : Accès 17 - Etage 2 - Salle 06)
Resit exam (05/03/27) 9:00 - 12:30
(St Martin : Accès 17 - Etage 1 - Salle 16)