  In the context of the introduction of intermittent renewable energies, we
propose to optimize the main variables of the control rods of a nuclear power
plant to improve its capability to load-follow. The design problem is a
black-box combinatorial optimization problem with expensive evaluation based on
a multi-physics simulator. Therefore, we use a parallel asynchronous
master-worker Evolutionary Algorithm scaling up to thousand computing units.
One main issue is the tuning of the algorithm parameters. A fitness landscape
analysis is conducted on this expensive real-world problem to show that it
would be possible to tune the mutation parameters according to the low-cost
estimation of the fitness landscape features.
