In this project, we are also interested in cases where the data of an optimization problem are not known with certainty, and it is therefore necessary to integrate this uncertainty in the model to be optimized. In this context, the goal is to determine which are called robust solutions, that is to say "good" for the different plausible values of the uncertain data. Our research here concerns robust optimization in the context of linear programming.
- Keywords : Polyhedral approach, Network design, Graph Theory, Probabilistic method, Robustness, Semi-definite positive programming, TDI (box-) system, Large problems, column generation, cutting plane algorithms
Permanent members : Denis Cornaz, Virginie Gabrel, Ararat Harutyunyan, A. Ridha Mahjoub, Cécile Murat.
ATER, (Post-)Doctorants : Charles Nourry, Isma Bentoumi, Hajer Ben Fekih.