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Solving the Earth Observing Satellite Constellation Scheduling Problem by Branch-and-Price

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Operations Research Proceedings 2010

Part of the book series: Operations Research Proceedings ((ORP))

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Abstract

An important economical issue for a space agency like China Center for Resource Satellite Data and Applications (CRESDA) is the optimization of the schedule of its earth observing satellites. The management of the constellation consists of selecting a feasible subset of requests and scheduling the observation activities of the satellites to acquire images as well as scheduling the download activities to transmit the images back to a set of ground stations, with the objective to maximize the summed rewards of the targets observed and image-downloaded. These selected and scheduled sequence of observations and downloads must comply with visibility time-windows, observing and downloading durations, satellite memory capacity, and minimum transition times between observations and downloads.

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References

  1. N. Bianchessi and G. Righini. Planning and scheduling algorithms for the COSMO-SkyMed constellation. Aerospace Science and Technology, 12(7): 535–544, 2008.

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  2. S. D. Florio. Performances optimization of remote sensing satellite constellations: a heuristic method. In Proc. of the 5th International Workshop on Planning and Scheduling for Space, 2006.

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  3. J. Frank, A. Jonsson, R. Morris, and D. Smith. Planning and scheduling for fleets of earth observing satellites. In Proc. of the 6th International Symposium on Artificial Intelligence, Robotics and Automation for Space, 2001.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Heidelberg, Heidelberg, Germany

    Pei Wang & Gerhard Reinelt

Authors
  1. Pei Wang
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  2. Gerhard Reinelt
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Corresponding author

Correspondence to Pei Wang .

Editor information

Editors and Affiliations

  1. , Fakultät für Betriebswirtschaft, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, Neubiberg, 85577, Bayern, Germany

    Bo Hu

  2. , Fakultät für Wirtschafts- und Organisati, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, Neubiberg, 85577, Bayern, Germany

    Karl Morasch

  3. Fakultät für Informatik, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, Neubiberg, 85577, Germany

    Stefan Pickl

  4. , Fakultät für Informatik, Universität der Bundeswehr München, Werner-Heisenberg-Weg 39, Neubiberg, 85577, Bayern, Germany

    Markus Siegle

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Wang, P., Reinelt, G. (2011). Solving the Earth Observing Satellite Constellation Scheduling Problem by Branch-and-Price. In: Hu, B., Morasch, K., Pickl, S., Siegle, M. (eds) Operations Research Proceedings 2010. Operations Research Proceedings. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20009-0_78

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