  In this paper the preliminary design of multiple gravity-assist trajectories
is formulated as a global optimization problem. An analysis of the structure of
the solution space reveals a strong multimodality, which is strictly dependent
on the complexity of the model. On the other hand it is shown how an
oversimplification could prevent finding potentially interesting solutions. A
trajectory model, which represents a compromise between model completeness and
optimization problem complexity is then presented. The exploration of the
resulting solution space is performed through a novel global search approach,
which hybridizes an evolutionary based algorithm with a systematic branching
strategy. This approach allows an efficient exploration of complex solution
domains by automatically balancing local convergence and global search. A
number of difficult multiple gravity-assist trajectory design cases
demonstrates the effectiveness of the proposed methodology.
