Automated Multigravity Assist Trajectory Planning with a Modified Ant Colony Algorithm

作者：Ceriotti Matteo^*; Vasile Massimiliano

来源：Journal of Aerospace Computing Information and Communication, 2010, 7(9): 261-293.

DOI：10.2514/1.48448

The paper presents an approach to transcribe a multigravity assist trajectory design problem into an integrated planning and scheduling problem. A modified Ant Colony Optimization algorithm is then used to generate optimal plans corresponding to optimal sequences of gravity assists and deep space maneuvers to reach a given destination. The modified Ant Colony Algorithm is based on a hybridization between standard ant colony optimization paradigms and a tabu-based heuristic. The scheduling algorithm is integrated into the trajectory model to provide a fast time-allocation of the events along the trajectory. The approach demonstrated to be very effective on a number of real trajectory design problems.

• 出版日期2010