Genetic algorithm optimization of lunar probe soft-landing trajectories

For lunar exploration missions such as soil sampling, payload instrumentation must safely descend to the lunar surface, a genetic algorithm (GA) optimization method was used to study constant-thrust amplitude lunar probe soft-landing trajectories. The parameterization technique was combined with the float encoding genetic algorithm (FGA) optimization method to analyze a two-body model to obtain minimum-fuel soft-landing trajectories. The simulation results show that application of the genetic algorithm for orbital control has no initial value problem and that the algorithm converges to the globally optimal solution.