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A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem

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  • Bingyu Song
  • Feng Yao
  • Yuning Chen
  • Yingguo Chen
  • Yingwu Chen

Abstract

The satellite image downlink scheduling problem (SIDSP) is included in satellite mission planning as an important part. A customer demand is finished only if the corresponding images are eventually downloaded. Due to the growing customer demands and the limited ground resources, SIDSP is an oversubscribed scheduling problem. In this paper, we investigate SIDSP with the case study of China’s commercial remote sensing satellite constellation (SuperView-1) and exploit the serial scheduling scheme for solving it. The idea is first determining a permutation of the downlink requests and then producing a schedule from the given ordered requests. A schedule generation algorithm (SGA) is proposed to assign the downlink time window for each scheduled request according to a given request permutation. A hybrid genetic algorithm (HGA) combined with neighborhood search is proposed to optimize the downlink request permutation with the purpose of maximizing the utility function. Experimental results on six groups of instances with different density demonstrate the effectiveness of the proposed approach.

Suggested Citation

  • Bingyu Song & Feng Yao & Yuning Chen & Yingguo Chen & Yingwu Chen, 2018. "A Hybrid Genetic Algorithm for Satellite Image Downlink Scheduling Problem," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-11, May.
    • Handle: RePEc:hin:jnddns:1531452
    DOI: 10.1155/2018/1531452
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    1. Karapetyan, Daniel & Mitrovic Minic, Snezana & Malladi, Krishna T. & Punnen, Abraham P., 2015. "Satellite downlink scheduling problem: A case study," Omega, Elsevier, vol. 53(C), pages 115-123.
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    4. 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.
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