TY - JOUR
T1 - Multi-objective optimal preliminary planning of multi-debris active removal mission in LEO
AU - Liu, Yong
AU - Yang, Jianan
AU - Wang, Yizhou
AU - Pan, Quan
AU - Yuan, Jianping
N1 - Publisher Copyright:
© 2017, Science China Press and Springer-Verlag Berlin Heidelberg.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - The goal of this paper is to develop a preliminary plan for a multi-nanosatellite active debris removal platform (MnADRP) for low-Earth-orbit (LEO) missions. A dynamic multi-objective traveling salesman problem (TSP) scheme is proposed in which three optimization objectives, i.e., the debris removal priority, the MnADRP orbital transfer energy, and the number of required nanosatellites are modeled respectively. A modified genetic algorithm (GA) is also proposed to solve the dynamic multi-objective TSP. Finally, numerical experiments involving partially real-world the debris data set are conducted to verify the efficacy of the proposed models and the solution method.
AB - The goal of this paper is to develop a preliminary plan for a multi-nanosatellite active debris removal platform (MnADRP) for low-Earth-orbit (LEO) missions. A dynamic multi-objective traveling salesman problem (TSP) scheme is proposed in which three optimization objectives, i.e., the debris removal priority, the MnADRP orbital transfer energy, and the number of required nanosatellites are modeled respectively. A modified genetic algorithm (GA) is also proposed to solve the dynamic multi-objective TSP. Finally, numerical experiments involving partially real-world the debris data set are conducted to verify the efficacy of the proposed models and the solution method.
KW - debris removal priority
KW - genetic algorithm
KW - multi-debris active removal
KW - multi-objective optimization
KW - optimal planning
UR - http://www.scopus.com/inward/record.url?scp=85019704991&partnerID=8YFLogxK
U2 - 10.1007/s11432-016-0566-7
DO - 10.1007/s11432-016-0566-7
M3 - 文章
AN - SCOPUS:85019704991
SN - 1674-733X
VL - 60
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 7
M1 - 072202
ER -