Robust handling of non‐linear constraints for GA optimization of aerodynamic shapes

Abstract

SUMMARYA new approach to the robust handling of non-linear constraints for GAs (genetic algorithms) optimization is proposed. A speciÿc feature of the approach consists of the change in the conventional search strategy by employing search paths which pass through both feasible and infeasible points (contrary to the traditional approach where only feasible points may be included in a path). The method (driven by full Navier-Stokes computations) was applied to the problem of multiobjective optimization of aerodynamic shapes subject to various geometrical and aerodynamic constraints. The results demonstrated that the method retains high robustness of conventional GAs while keeping CFD computational volume to an acceptable level, which allowed the algorithm to be used in a demanding engineering environment.

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