Gtoc9: Results From The Jet Propulsion Laboratory (Team Jpl)

Asteroid Flyby Cycler Trajectory Design Using Deep Neural Networks

“…Global trajectory optimization problems with multiple flybys essentially involve two optimization problems: a nonlinear optimal control problem that optimizes the trajectory for a given flyby sequence and a combinatorial optimization problem to choose the sequence of the flybys. Recent studies have proposed global trajectory optimization methods utilizing population-based metaheuristics [6][7][8]. Englander et al have applied their evolutionary algorithmbased method to NASA's Lucy mission, which visits multiple Trojan asteroids [1].…”