An Evolutionary Multi-Architecture Multi-Objective Optimization Algorithm for Design Space Exploration
Christopher P. Frank, Renaud A. Marlier, Olivia J. Pinon-Fischer, Dimitri N. Mavris · 57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference · 2016
The increasing complexity of future aerospace vehicles gives rise to large combinatorial spaces of possible configurations for which no baseline has been established. To ensure that the best concept is selected, the entire design space has to be explored. In addition, the presence of evolving requirements’ uncertainty due to the lack of experience and established regulations requires flexible decision-making techniques to be implemented to alleviate the risks inherent to the launch of new programs. To address these challenges, a new evolutionary multi-architecture multi-objective optimization algorithm is presented. The proposed approach allows designers to efficiently and exhaustively generate variable-oriented architectures that can be further optimized and compared. It provides a dynamic decision-making environment able to identify trends and trade-offs, while also prioritizing designs. The application of the proposed methodology on suborbital vehicles highlights key promising technological enablers, which can be leveraged to design high-performance and robust concepts.