Genetic Algorithm, figuring out the optimal solution problem of active removal of space debris

Abstract

Space junk, one of the man-made pollution, is destroying the satellite's safety, ultimately making low earth orbit (LEO) unusable. Many countries, such as Japan and U.S., have been proposed many different methods for remediation of the orbital debris environment over the years, including the use of lasers, electro-dynamic or momentum exchange tethers, tugs, and other, more exotic methods. Firstly, this paper picks out five removal methods with the highest feasibility and reliability. These five methods have the ability to clean space junk in different heights near-earth orbit, and in a few years these will become the mainstream methods to make the space cleaning. Secondly, this paper establishes a model called the Long-term Model which is constructed to figure out the optimal solution problem of active removal of space debris by combining those five methods. Following the three principles drafted by NASA and ESA, 10 hot spots in given orbits should be removed by the combinations of five methods every year in order to reduce the spacecraft’s risk. In detail, based on the Genetic Algorithm and taking small disturbance into account, the model has derived the approximate optimal solution by randomization test and iteration so as to figure out the best combination of methods.