Performance comparison of evolutionary algorithms applied to hybrid rocket problem

Optimizer is an essence in design-informatics to efficiently obtain nondominated solutions. In the present study, the best optimizer is decided through the competition for the mathematical standard test functions and is also applied to a conceptual design problem of simple single-stage hybrid rocket as the real-world problem. Consequently, a hybrid method between differential evolution and genetic algorithm has good exploration performance. Moreover, the principal component analysis blended crossover and the confidence interval based crossover have good capability on the hybrid method between differential evolution and genetic algorithm.