Application of a Genetic Algorithm to the Optimization of Hybrid Rockets

A Genetic Algorithm (GA) optimization technique has been successfully applied to the design of a large hybrid rocket booster. Optimizations on gross liftoff weight and total inert weight have been carried out using the Hybrid ROcket Sizing (HYROCS) code developed at Purdue University. The GA was able to optimize designs which contained both continuous and discrete variables. Discrete variables which were optimized included the propellant combination and the number of fuel ports, while continuous variables such as tank and chamber pressure, and oxidizer massflux level were simultaneously optimized using the GA procedure. Results with optimal or very-nearly optimal solutions have been verified on a design space which happened to contain a very broad, shallow minimum in weight.