Title: Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO,
Abstract: The design of spacecraft trajectories for missions visiting multiple
celestial bodies is here framed as a multi-objective bilevel optimization
problem. A comparative study is performed to assess the performance of
different Beam Search algorithms at tackling the combinatorial problem of
finding the ideal sequence of bodies. Special focus is placed on the
development of a new hybridization between Beam Search and the Population-based
Ant Colony Optimization algorithm. An experimental evaluation shows all
algorithms achieving exceptional performance on a hard benchmark problem. It is
found that a properly tuned deterministic Beam Search always outperforms the
remaining variants. Beam P-ACO, however, demonstrates lower parameter
sensitivity, while offering superior worst-case performance. Being an anytime
algorithm, it is then found to be the preferable choice for certain practical
applications.