Effective multi-objective optimization for aerodynamic and stealthy performance of tactical missiles

A new effective multi-objective optimization method was employed to solve the aerodynamic and stealthy performance optimization of tactical missile problem. Physical programming was selected to translate the multi-objective problem into the single objective problem. Genetic algorithm (GA) was applied to carrying on the design space search. Variable selection and radial basis function (RBF) were contributed to reducing the design variable space dimension and the number of high fidelity model evaluations. Then, the aerodynamic and stealthy performance optimization of a quasi BGM-109 model was chosen as an example to deliver the whole optimization steps and verify the correctness of the method. The optimization task is to minimize the drag coefficient and the heading radar cross section (RCS) subject to the aerodynamic performance constraint, namely the lift coefficient has to be no less than the initial value. Through application to engineering case, the computational cost of the proposed method decreases by 83% compared to that of GA, while two methods has nearly identical performance.