Overall Mission Trajectory Optimization for Manned Lunar Landing Mission Using a Hybrid Algorithm

Aimed at trajectory optimization problem for manned lunar landing mission, an overall mission optimization model was established, through which translunar trajectory, lunar parking orbit and transearth trajectory were designed optimally based on patched-conic technique. A hybrid approach combined genetic algorithm (GA) and sequential quadratic programming (SQP) was proposed to solve the optimization problem, in which the GA was used to find an initial guess for SQP, and the latter was employed to obtain the optimal solution. The global convergence ability of the hybrid algorithm was verified by dividing the overall mission into submissions for optimization. The simulation results validate the proposed approach.