The flight performance of a ram jet- powered missile is improved through the use of an automated optimization
loop relying on computational-fluid-dynamics tools. A generic supersonic airbreathing missile is first described,
and its performance is assessed for a representatixe mission using Reynolds-averaged Navier-Stokes computations
for aerodynamics prediction and theoretical engine performance models. Tlıe loop links together an optimization
algorithm with an aerodynamic software computing the aerodynamic balance of the missile. Several optimizations
are performed using different global algorithms such as simplex, evolutionary strategies, or genetic algorithms.
The first ones are mono-objective: for each point of the mission (acceleration, cruise, and maneuver), the best inlet
shape has to be found. Then multiobjectıve optimızatıons are performed in order to find the pareto front, that is,
the best set of shapes satisfying the whole mission
