Comparative analysis of genetic crossover operators for the optimization of impulsive multi-rendezvous trajectories

This paper investigates the use of a genetic algorithm for the optimization of an impulsive multi- rendezvous trajectory. The aim is to minimize the overall mission , while performing a complete tour of a prescribed set of targets, which move on the same orbital plane at slightly different altitudes. A sub-optimal four-impulse strategy is proposed for rapidly evaluating the cost of each leg connecting two assigned consecutive targets. The genetic algorithm is exploited to define the optimal target sequence with encounter times discretized over an assigned time grid. The solution is encoded as an augmented-size permutation, allowing for a finer time discretization. Several permutation-preserving crossover operators are considered in the present work. Their effectiveness for the impulsive multi-rendezvous mission is investigated by means of a thorough analysis.