Self-regulating Multi-agent System for Multi-disciplinary Optimisation Process

This article presents a multi-agent method to tackle multidisciplinary optimisation, based on the notions of cooperation and self-regulation. It is focused on the preliminary aircraft design, which is a complex compromise. In our approach several cooperative agents collectively act to achieve a common goal, i.e. optimising a multi-objective function, even if the environment of the system (the user's requirements) changes during the solving process. In MASCODE, one agent encapsulates one discipline and is designed individually without considering the dependencies with the others. So the computation is conceptually distributed without central control. Experimental results including efficiency comparison with the classical FSQP method are presented, and show that the adaptive behaviour of MASCODE provides new capabilities to understand and manage the complexity of the preliminary aircraft design.