The theory of optimal experimental designs is an important branch of statistics,

which aims at choosing optimally the experimental conditions of

statistical trials to be performed. This domain raises many interesting optimization problems,

some of which can be solved by second-order cone or semidefinite programming.

In this project, we want to develop new algorithms based on mathematical programming

to compute optimal experimental designs in various contexts, and promote the use of these methods.