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Timeline Club: An optimization algorithm for solving multiple debris removal missions of the time-dependent traveling salesman problem model

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Abstract

With the increase of space debris, space debris removal has gradually become a major issue to address by worldwide space agencies. Multiple debris removal missions, in which multiple debris objects are removed in a single mission, are an economical approach to purify the space environment. Such missions can be considered typical time-dependent traveling salesman problems (TDTSPs). In this study, an intelligent global optimization algorithm called Timeline Club Optimization (TCO) is proposed to solve multiple debris removal missions of the TDTSP model. TCO adopts the traditional ant colony optimization (ACO) framework and replaces the pheromone matrix of the ACO with a new structure called the Timeline Club. The Timeline Club records which debris object to be removed next at a certain moment from elitist solutions and decides the probability criterion to generate debris sequences in new solutions. Two hypothetical scenarios, the Iridium-33 mission and the GTOC9 mission, are considered in this study. Simulation results show that TCO offers better performance than those of beam search, ant colony optimization, and the genetic algorithm in multiple debris removal missions of the TDTSP model.

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Acknowledgements

This research was supported by the National Key R&D Program of China (No. 2019YFA0706500).

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Authors and Affiliations

  1. School of Aerospace Engineering, Tsinghua University, Beijing, 100084, China

    Nan Zhang, Zhong Zhang & Hexi Baoyin

Authors
  1. Nan Zhang
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  2. Zhong Zhang
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  3. Hexi Baoyin
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Corresponding author

Correspondence to Hexi Baoyin.

Additional information

Nan Zhang received his bachelor degree in engineering mechanics, in 2019, from Tsinghua University, Beijing, China. He was a visiting student at Lunar and Planetary Laboratory in the University of Arizona from October 2018 to February 2019. He is now pursuing his Ph.D. degree in School of Aerospace Engineering, Tsinghua University. His research interests are focused on intelligent optimization algorithms for multitarget detection and trajectory optimization.

Zhong Zhang received his bachelor degree in aerospace engineering from Tsinghua University, Beijing, China, in 2019. He is currently a Ph.D. student in School of Aerospace Engineering, Tsinghua University. His research interests fall under the combinatorial optimization problems.

Hexi Baoyin, professor in School of Aerospace Engineering, Tsinghua University. His current research interests include orbit theory in irregular gravitational fields and interplanetary mission analysis and optimization.

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Zhang, N., Zhang, Z. & Baoyin, H. Timeline Club: An optimization algorithm for solving multiple debris removal missions of the time-dependent traveling salesman problem model. Astrodyn 6, 219–234 (2022). https://doi.org/10.1007/s42064-021-0107-z

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