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Space-Ground TT&C Resources Integrated Scheduling Based on the Hybrid Ant Colony Optimization

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Proceedings of the 28th Conference of Spacecraft TT&C Technology in China (TT&C 2016)

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Abstract

Space-ground TT&C resource integrated scheduling problem (TTCRISP) is a representative of large combinative optimization problem, and its optimization process is very complicated, single ant colony optimization (ACO) strategy has disadvantage of low efficiency and poor performance. For this reason, this paper proposes two different serial structure hybrid approaches which combine ACO with genetic algorithm (GA) to tackle TTCRISP. GA is used to accelerate the low optimization efficiency due to the lack of pheromone in the early processing stage of ACO and to prevent premature convergence. Results indicate that the new method performs better than the previously presented methods from the subjective and objective viewpoints and is a viable and effective approach for the space-ground TT&C resource integrated scheduling problem.

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Acknowledgements

Thanks are due to the State Key Laboratory of Astronautic Dynamics for their supporting this work and International GNSS monitoring and assessment system (iGMAS) for providing the observation data (www.igmas.org). This work is supported by National 973 Program of China (NO.613237201506), National 863 Program of China (NO.2014AA7013035) and the Open Research Fund of the State Key Laboratory of Astronautic Dynamics under Grant 2013GKJ11-ADL.

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Authors and Affiliations

  1. State Key Laboratory of Astronautic Dynamics, Xi’an, 710043, China

    Zexi Li, Jing Li & Wenting Mu

Authors
  1. Zexi Li
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  2. Jing Li
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  3. Wenting Mu
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Corresponding author

Correspondence to Zexi Li .

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Editors and Affiliations

  1. Chinese Academy of Engineering, Beijing, China

    Rongjun Shen

  2. Beijing Institute of Tracking and Telecommunications Technology, Beijing, China

    Guangliang Dong

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© 2018 Tsinghua University Press, Beijing and Springer Nature Singapore Pte Ltd.

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Li, Z., Li, J., Mu, W. (2018). Space-Ground TT&C Resources Integrated Scheduling Based on the Hybrid Ant Colony Optimization. In: Shen, R., Dong, G. (eds) Proceedings of the 28th Conference of Spacecraft TT&C Technology in China. TT&C 2016. Lecture Notes in Electrical Engineering, vol 445. Springer, Singapore. https://doi.org/10.1007/978-981-10-4837-1_15

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  • DOI: https://doi.org/10.1007/978-981-10-4837-1_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4836-4

  • Online ISBN: 978-981-10-4837-1

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