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Automatic satisfaction of constraints set in aircraft sizing studies

1. Abstract Aircraft sizing studies consist in determining characteristics of an aircraft, starting from a set of requirements. These studies can be summarized as global optimization problems under constraints, which express requirements. In this paper, we only consider the constraints satisfaction problem. Our aim is to automatically produce large amounts of design points satisfying all the constraints, despite frequent evaluation failures. This problem can potentially be solved in two ways: gradient-based methods and stochastic methods. We show that our dedicated implementation of genetic algorithms exhibits good results in terms of robustness and speed. We compare our genetic algorithms implementation with a gold standard method in constraints satisfaction: FSQP. Our results are very promising: genetic algorithms achieve convergence 80% of cases, and are fast compared to the time an engineer needs to exhibit such points, producing in average one admissible point every 15 minutes. 2.