Hybrid Optimization for a Combinatorial Aircraft Design Problem

Economic and environmental considerations call for highly sophisticated new aircraft designs. Numerical optimization procedures can aid the designer in searching for the best available design. However, an aircraft optimization problem is a combinatorial problem which consists of continuous and discrete design variables. The latter stand for both, design choices and the possible application of new technologies that might enable a significant advantage compared to conventional designs. This paper approaches this problem with a hybrid optimization algorithm, i.e. the use of two di!erent o ptimization algorithms in a single process. Here, this is a combination of a binary-coded genetic algorithm and a gradient based method as the hybrid optimizer. Applied to the design of a 150-seat aircraft, the algorithm identified three promising configurations. They operate at low cost and have a reduced environmental impact compared to current aircraft with a similar mission.