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Numerical Optimization of ESA’s Messenger Space Mission Benchmark

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Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

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Abstract

The design and optimization of interplanetary space mission trajectories is known to be a difficult challenge. The trajectory of the Messenger mission (launched by NASA in 2004) is one of the most complex ones ever created. The European Space Agency (ESA) makes available a numerical optimization benchmark which resembles an accurate model of Messengers full mission trajectory. This contribution presents an optimization approach which is capable to (robustly) solve ESA’s Messenger full mission benchmark to its putative global solution within 24 h run time on a moderate sized computer cluster. The considered algorithm, named MXHPC, is a parallelization framework for the MIDACO optimization algorithm which is an evolutionary method particularly suited for space trajectory design. The presented results demonstrate the effectiveness of evolutionary computing for complex real-world problems which have been previously considered intractable.

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Notes

  1. 1.

    Note that this is the same value for the FOCUS parameter as used for refinement runs in [20].

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Acknowledgement

The authors are grateful to the Advanced Concept Team (ACT) of the European Space Agency (ESA) and particular Dario Izzo for providing and maintaining the GTOP database. The first author would further like to thank the European Space Agency (ESA-ESTEC/Contract No. 21943/08/NL/ST) and EADS Astrium Ltd. (Stevenage, UK) for their support on the MIDACO development.

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Authors and Affiliations

  1. Information Initiative Center, Hokkaido University, Sapporo, 060-0811, Japan

    Martin Schlueter & Masaharu Munetomo

  2. RIKEN Advanced Institute for Computational Science, 7-1-26 Minatojima-minami-machi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan

    Mohamed Wahib

Authors
  1. Martin Schlueter
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  2. Mohamed Wahib
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  3. Masaharu Munetomo
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Corresponding author

Correspondence to Martin Schlueter .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Schlueter, M., Wahib, M., Munetomo, M. (2017). Numerical Optimization of ESA’s Messenger Space Mission Benchmark. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_47

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  • DOI: https://doi.org/10.1007/978-3-319-55849-3_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55848-6

  • Online ISBN: 978-3-319-55849-3

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