Mathieu Balesdent

The preliminary design and optimization of aerospace systems often requires to make architectural and technological choices and to perform computationally expensive numerical simulations. In early design phases, the decision makers may be interested in obtaining a set of valuable solutions presenting a diversity of characteristics. This paper proposes two approaches tackling these challenges by formulating and solving a particular optimization problem. The latter is called Conditional Search-Space Problem because architectural and technological choices are represented by design variables, called conditional, which are acting on the structure of the optimization problem (e.g., number of design variables and constraints). To produce a broad diversity of solutions, a Quality-Diversity (QD) algorithm adapted to deal with conditional variables and expensive functions is developed. The proposed methods consist in decomposing the optimization problem in several subproblems that have a non-conditional structure. A Bayesian optimization strategy coupled with a QD algorithm is used to search for potential solutions among the subproblems. The most performing potential solutions are then evaluated with the exact functions. The methodology is tested on two analytical and an aerospace system design problems.

Optimal layout problems consist in positioning a given number of components in order to minimize an objective function while satisfying geometrical or functional constraints. Such kinds of problems appear in the design process of aerospace systems such as satellite or spacecraft design. These problems are NP-hard, highly constrained and dimensional. This paper describes a two-stage algorithm combining a genetic algorithm and a quasi-physical approach based on a virtual-force system in order to solve multi-container optimal layout problems such as satellite modules. In the proposed approach, a genetic algorithm assigns the components to the containers while a quasi-physical algorithm based on a virtual-force system is developed for positioning the components in the assigned containers. The proposed algorithm is experimented and validated on the satellite module layout problem benchmark. Its global performance is compared with previous algorithms from the literature.