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Performance Comparison of Stochastic Search Algorithms on the Interplanetary Gravity-Assist Trajectory Problem

机译:随机搜索算法在行星际重力辅助弹道问题上的性能比较

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DE and PSO proved robust given their reliability record in the random seed analysis, and they were able to locate the optimum in relatively few function evaluations. Furthermore, both DE and PSO proved to be viable tools for solving the interplanetary trajectory problem for these scenarios, as each was able to identify candidate trajectories without an excessive computational cost. Granted, the use of a single gravity assist in an interplanetary trajectory problem is not considered a daunting task. DE's performance in this case makes it an attractive means to minimize Δv on more involved multiple gravity-assist problems requiring n-body gravity fields. Although this work uses an epoch of 01 January 2005 00:00 UT, this epoch was chosen arbitrarily. Upon inspection of the final results, it is the author's opinion that this analysis would hold up for any other chosen epoch time.
机译:鉴于DE和PSO在随机种子分析中的可靠性记录,它们被证明是可靠的,并且它们能够在相对较少的功能评估中找到最佳位置。此外,事实证明,DE和PSO都是解决这些场景的行星际轨迹问题的可行工具,因为它们每个人都能够识别候选轨迹而无需过多的计算成本。诚然,在行星际轨道问题中使用单个重力辅助装置并不是一项艰巨的任务。在这种情况下,DE的性能使其成为一种有吸引力的方法,可以将涉及n个重力场的更多涉及多个重力辅助问题的Δv最小化。尽管本工作使用的时间为2005年1月1日UT 00:00,但该时间是任意选择的。在检查最终结果后,作者认为此分析将在其他任何选定的时间段内维持下去。

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