  In the preliminary trajectory design of the multi-target rendezvous problem,
a model that can quickly estimate the cost of the orbital transfer is
essential. The estimation of the transfer time using solar sail between two
arbitrary orbits is difficult and usually requires to solve an optimal control
problem. Inspired by the successful applications of the deep neural network in
nonlinear regression, this work explores the possibility and effectiveness of
mapping the transfer time for solar sail from the orbital characteristics using
the deep neural network. Furthermore, the Monte Carlo Tree Search method is
investigated and used to search the optimal sequence considering a
multi-asteroid exploration problem. The obtained sequences from preliminary
design will be solved and verified by sequentially solving the optimal control
problem. Two examples of different application backgrounds validate the
effectiveness of the proposed approach.
