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Optimal trajectory planning for multiple asteroid tour mission by means of an incremental bio-inspired tree search algorithm

机译:通过增量生物启发式树形搜索算法,对多个小行星游览任务进行最优轨迹规划

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摘要

In this paper, a combinatorial optimisation algorithm inspired by the Physarum Polycephalum mould is presented and applied to the optimal trajectory planning of a multiple asteroid tour mission. The Automatic Incremental Decision Making And Planning (AIDMAP) algorithm is capable of solving complex discrete decision making problems with the use of the growth and exploration of the decision network. The stochastic AIDMAP algorithm has been tested on two discrete astrodynamic decision making problems of increased complexity and compared in terms of accuracy and computational cost to its deterministic counterpart. The results obtained for a mission to the Atira asteroids and to the Main Asteroid Belt show that this non-deterministic algorithm is a good alternative to the use of traditional deterministic combinatorial solvers, as the computational cost scales better with the complexity of the problem.
机译:在本文中,提出了一种由Physarum Polycephalum模具启发的组合优化算法,并将其应用于多小行星巡回任务的最优轨迹规划。自动增量决策制定和计划(AIDMAP)算法能够利用决策网络的增长和探索来解决复杂的离散决策问题。随机AIDMAP算法已针对两个复杂性增加的离散天体动力学决策问题进行了测试,并在准确性和计算成本方面与确定性同类算法进行了比较。一次对Atira小行星和主小行星带的飞行任务获得的结果表明,这种非确定性算法是使用传统确定性组合解算器的很好选择,因为计算成本随着问题的复杂性而更好地扩展。

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