Abstract
Genetic algorithms have gained popularity as effective search procedures for obtaining solutions to traditionally difficult space mission optimization problems. In this paper, a hybrid optimization method is described that integrates a multi-objective genetic algorithm with a calculus-of-variations-based low-thrust trajectory optimizer. Fronts of Pareto optimal trajectories are generated and novel trajectories identified for both Earth–Mars and Earth–Mercury missions.
