In order to improve space debris removal efficiency, a method of removing multiple debris by one satellite has been studied. Since there are many debris currently around the Earth, the number of combinations of removal order becomes enormous and it is difficult to strictly obtain the optimal solution. Therefore, an efficient algorithm to optimize the trajectory of the debris removal satellite is required. The active debris removal optimization problem can be thought of as an application of the traveling salesman problem, and the application of the evolutionary algorithm can be considered. In this research, we propose a method to optimize this by using evolutionary computation, assuming a mission scenario in which a certain number of debris are selected from debris to be removed and are continuously engaged. The objective function was aimed at minimizing the total ΔV of removal satellites and maximizing the Radar Cross-Section (RCS) of eliminated debris. For optimization, we apply two evolutionary computation algorithms of NSGA-II and MOEA/D, to investigate the difference in optimization performance and to acquire knowledge on the target optimization problem.
内容記述
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内容記述（英）
Physical characteristics: Original contains color illustrations
Optimization of a Trajectory to Remove Multiple Space Debris Using Evolutionary Computation
AA1830034054.pdf
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