Complex systems design involves numerous disciplines, for example for aircraft design: weight, range, aerodynamic and operating cost estimations intervene. In addition to the multidisciplinary aspect, manufacturers and end-users have different objectives on the product. Thus, during this design process several compromises are carried out in order to specify the high-level design producing expected product performances. These compromises are difficult to achieve, because constraints are numerous and interdependent. The design can be taken into account at different levels of granularity and in general, the approach is top down and the coherence between the different levels is not ensured.

Reducing uncertainties and development times are two of the main challenges for aircraft engine designers. In particular, multi-disciplinary design is a very time-consuming process. Effectively this kind of design must solve antagonistic objectives handled by different specialists and it is often a challenge to converge towards a satisfying trade-off between disciplines within the planned time span.The project outcomes will thus have a direct impact on reducing the engine performance uncertainties and thereby improving competitiveness.

In ID4CS, there are strong relations between optimization, uncertainties and multi-agent systems domains. In the context of a design problem to solve, the multi-agent technique enables optimization and uncertainties approaches to work together and to cooperate. The knowledge about how to cooperate is given by the multi-agent and the knowledge about how to solve the design problem is given by optimization and uncertainties domains. This collaboration between the 3 domains constitutes an original work.