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Uplink Scheduling of Navigation Constellation Based on Immune Genetic Algorithm

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  • Yinyin Tang
  • Yueke Wang
  • Jianyun Chen
  • Xianbin Li

Abstract

The uplink of navigation data as satellite ephemeris is a complex satellite range scheduling problem. Large–scale optimal problems cannot be tackled using traditional heuristic methods, and the efficiency of standard genetic algorithm is unsatisfactory. We propose a multi-objective immune genetic algorithm (IGA) for uplink scheduling of navigation constellation. The method focuses on balance traffic and maximum task objects based on satellite-ground index encoding method, individual diversity evaluation and memory library. Numerical results show that the multi–hierarchical encoding method can improve the computation efficiency, the fuzzy deviation toleration method can speed up convergence, and the method can achieve the balance target with a negligible loss in task number (approximately 2.98%). The proposed algorithm is a general method and thus can be used in similar problems.

Suggested Citation

  • Yinyin Tang & Yueke Wang & Jianyun Chen & Xianbin Li, 2016. "Uplink Scheduling of Navigation Constellation Based on Immune Genetic Algorithm," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0164730
    DOI: 10.1371/journal.pone.0164730
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