Bayesian Quality-Diversity approaches for constrained optimization problems with mixed continuous, discrete and categorical variables

Complex system design problems, such as those involved in aerospace engineering, require the use of numerically costly simulation codes in order to predict the performance of the system to be designed. In this context, these codes are often embedded into an optimization process to provide the best design while satisfying the design constraints. Recently, new approaches, called Quality-Diversity, have been proposed in order to enhance the exploration of the design space and to provide a set of optimal diversified solutions …

aerospace bayesian categorical context continuous cs.lg design diversity embedded engineering math.oc mixed optimization performance process quality simulation variables