Optimization of Lunar Soft Landing Trajectory Based on Adaptive Simulated Annealing Genetic Algorithm
Shijie Xu · Acta Aeronautica Et Astronautica Sinica · 2007
An adaptive simulated annealing genetic algorithm(ASAGA)by combining adaptive genetic algorithm(AGA)with simulated annealing algorithm(SAA)is develped.The new algorithm provides not only with strong global search capability of AGA,but also with strong local search capability of SAA.For optimization of lunar soft landing trajectory,a new parameterized method is used to convert a trajectory optimization problem into a nonlinear programming problem(NLP),and then the proposed ASAGA is applied.The simulation results indicate that the ASAGA takes on fast convergence rate and high optimization precision,moreover it avoids many shortcomings such as initial value sensitivity,ill-conditioned gradient and local convergence and so on.It can obtain global optimum trajectory.