Aerospace Design Optimization Using a Real Coded Genetic Algorithm

Abstract

This study demonstrates the advantages of using a real coded genetic algorithm (GA) for aerospace engineering design applications. A real coded GA was written from first principles for this study and the source code can be seen in Appendix A. The GA runs steady state, meaning that after every function evaluation a tournament scheme determines the worst performer and that worst performer is then thrown out and replaced by a new member that has been evaluated. The new member is produced by mating two successful parents through a crossover routine, and then mutating that new member. For this study three different preliminary design studies were conducted using both a binary and a real coded GA including a Single Stage Solid Propellant Missile Systems Design, a Two Stage Solid Propellant Missile Systems Design and a Single Stage Liquid Propellant Missile Systems Design.