Integration of Genetic Algorithms Neural Networks and Classical Optimiser for Complex Fluid dynamics Problems

This paper describes the combination of several optimization technologies that can be used to tackle challenging design problems. A The approach, that uses a multi-objective genetic algorithm, a neural network, and a gradient-based optimizer, is Hrst outlined with the help of a computationally inexpensive mathematical test function. Then the methodology is applied to the design of a sailin yacht fin 0 keel, coupling the optimization codes to 3D Navier-Stokes simulations. To perform the multi-objective optimization task a parallel computer is employed.