Mathematical Optimization, Stochastic Modelling and Statistics

Team Mathematical Optimization, Stochastic Modelling and Statistics

The research of OptimAl focuses on the development of mathematical tools for the modelling of random systems (inference, data analysis), as well as the resolution and analysis of optimization problems (combinatorial optimization and stochastic control) or performance evaluation (statistics).

Team leader : Boris Detienne

Informations complémentaires

Research Themes

Statistics and Probability

Multivariate analysis, dimension reduction
Inferential statistics. Application areas: environment (ecology, climate), reliability
Design and analysis of stochastic processes for various applications (including branching processes and piecewise deterministic processes)

Operations Research, Mathematical Optimization

Extended formulations for mixed-integer linear programs: Dantzig-Wolfe, Benders, flow reformulations
Iterative formulation generation algorithms: column generation, cut generation, branch-and-X
Multi-stage optimization under uncertainty: robust optimization, stochastic programming
Operations research: planning and scheduling, packing, vehicle routing, industrial applications
Theoretical and numerical methods for stochastic optimal control problems, mathematical analysis of asymptotic behaviour and robustness of controlled stochastic systems, game theory

Seminaires réguliers

The Mathematical Optimization, Stochastic Modelling and Statistics seminar (organizers: Ayse Nur Arslan and Frédéric Barraquand) on Thursdays at 11:00 am in room 2.