Aerospace Design Optimization Using A Compound Repulsive Particle Swarm

Abstract

This study compares contemporary design optimization algorithms for use in missile design applications. The engineering design problem for this study is the development of a desired single stage solid propellant missile system. The methods are used independently to match a prescribed set of parameters defining the missile’s geometry and propellant characteristics. For this development, three different design optimization techniques are considered: a real-coded genetic algorithm (GA), a binary GA, and a Repulsive Particle Swarm Optimizer (RPSO). Since there is not nearly as much known about how the RPSO operates compared to the GA’s, an extensive effort was invested in the study of how changing RPSO controlling parameters would affect its operation. Also, a new hybrid optimizer has been developed for this study involving a separate Particle Swarm imbedded within the standard RPSO. The algorithms are compared based on their speed and effectiveness in solving the design problem, with the figure of merit being a factor based on the desired performance goals for the missile.