A single-stage launch vehicle with hybrid rocket engine, which uses solid fuel and liquid oxidizer, has been being studied and developed as a next-generation rocket for scientific observation due to the advantages as low cost, safety, re-ignition, and reduced pollution. Therefore, the knowledge regarding hybrid rocket system has been being gained through the forepart of the conceptual design using design informatics. In the present study, the practical problem defined by using three objective functions and seven design variables for the aurora observation is treated so as to contribute the real world using evolutionary computation and data mining for the field of aerospace engineering. The primary objective of the design in the present study is that the sufficient down range and the duration time in the lower thermosphere are sufficiently achieved for the aurora scientific observation whereas the initial gross weight is held down. A hybrid rocket engine uses polypropylene as solid fuel and liquid oxygen as liquid oxidizer, and the condition of single-time ignition is assumed in sequence in order to quantitatively investigate the ascendancy of multi-time ignition. An evolutionary hybrid computation between the differential evolution and the genetic algorithm is employed for the multidisciplinary design optimization. A self-organizing map is used for the data mining technique in order to extract global design information. Consequently, the design information regarding the tradeoffs among the objective functions, the behaviors of the design variables in the design space to become the nondominated solutions, and the implication of the design variables for the objective functions has been obtained in order to quantitatively differentiate the advantage of hybrid rocket engine. Moreover, the next assignments were also revealed.