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Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm

Author

Listed:
  • Zhang Ye
  • Hu Xiaoxuan
  • Zhu Waiming
  • Jin Peng

    (School of Management, Hefei University of Technology, Hefei230009, China)

Abstract

This paper addresses the integrated Earth observation satellite scheduling problem. It is a complicated problem because observing and downloading operations are both involved. We use an acyclic directed graph model to describe the observing and downloading integrated scheduling problem. Based on the model which considering energy constraints and storage capacity constraints, we develop an efficient solving method using a novel quantum genetic algorithm. We design a new encoding and decoding scheme that can generate feasible solution and increase the diversity of the population. The results of the simulation experiments show that the proposed method solves the integrated Earth observation satellite scheduling problem with good performance and outperforms the genetic algorithm and greedy algorithm on all instances.

Suggested Citation

  • Zhang Ye & Hu Xiaoxuan & Zhu Waiming & Jin Peng, 2018. "Solving the Observing and Downloading Integrated Scheduling Problem of Earth Observation Satellite with a Quantum Genetic Algorithm," Journal of Systems Science and Information, De Gruyter, vol. 6(5), pages 399-420, October.
    • Handle: RePEc:bpj:jossai:v:6:y:2018:i:5:p:399-420:n:2
    DOI: 10.21078/JSSI-2018-399-22
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    References listed on IDEAS

    as
    1. Tangpattanakul, Panwadee & Jozefowiez, Nicolas & Lopez, Pierre, 2015. "A multi-objective local search heuristic for scheduling Earth observations taken by an agile satellite," European Journal of Operational Research, Elsevier, vol. 245(2), pages 542-554.
    2. Gabrel, Virginie & Vanderpooten, Daniel, 2002. "Enumeration and interactive selection of efficient paths in a multiple criteria graph for scheduling an earth observing satellite," European Journal of Operational Research, Elsevier, vol. 139(3), pages 533-542, June.
    3. Virginie Gabrel, 2006. "Strengthened 0-1 linear formulation for the daily satellite mission planning," Journal of Combinatorial Optimization, Springer, vol. 11(3), pages 341-346, May.
    4. Hall, Nicholas G. & Magazine, Michael J., 1994. "Maximizing the value of a space mission," European Journal of Operational Research, Elsevier, vol. 78(2), pages 224-241, October.
    5. Virginie Gabrel & Alain Moulet & Cécile Murat & Vangelis Paschos, 1997. "A new single model and derived algorithms for the satellite shot planning problem using graph theory concepts," Annals of Operations Research, Springer, vol. 69(0), pages 115-134, January.
    6. Bianchessi, Nicola & Cordeau, Jean-Francois & Desrosiers, Jacques & Laporte, Gilbert & Raymond, Vincent, 2007. "A heuristic for the multi-satellite, multi-orbit and multi-user management of Earth observation satellites," European Journal of Operational Research, Elsevier, vol. 177(2), pages 750-762, March.
    7. William J. Wolfe & Stephen E. Sorensen, 2000. "Three Scheduling Algorithms Applied to the Earth Observing Systems Domain," Management Science, INFORMS, vol. 46(1), pages 148-166, January.
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