Particle Swarm Optimization Applied to Space Trajectories

Abstract

The particle swarm optimization technique is a population-based stochastic method developed in recent years and successfully applied in several fields of research. It represents a very intuitive (and easy to program) methodology for global optimization, inspired by the behavior of bird flocks while searching for food. The particle swarm optimization technique attempts to take advantage of the mechanism of information sharing that affects the overall behavior of a swarm, with the intent of determining the optimal values of the unknown parameters of the problem under consideration. In this research the method is applied to a variety of space trajectory optimization problems, i.e., the determination of periodic orbits in the context of the circular restricted three-body problem, and the optimization of (impulsive and finite thrust) orbital transfers. Despite its simplicity and intuitiveness, the particle swarm algorithm proves to be quite effective in finding the optimal solution to all of the applications considered in the paper, with great numerical accuracy.