Design of optimal multiple-impulsive rendezvous trajectory using genetic algorithms

The optimal multiple-impulsive rendezvous trajectories were designed using genetic algorithms to solve the rendezvous problem of minimum fuel and time-fuel combinatorial optimization. The magnitudes, directions and burn times of the optimal impulses were coded into genetic algorithms, and the fitness functions were designed to evaluate the final states and necessary conditions. The method was used for four test cases, including the two-impulse rendezvous, the optimal two-impulse rendezvous with initial coastings, the optimal three-impulse rendezvous and time-fuel combinatorial optimal three-impulse rendezvous. Compared with the precision optimal solutions solved by Newton iterative algorithm, the GA solutions are more precise, thus the method in the paper is proved to be correct and effective.