Abstract
This contribution presents new state-of-the-art results for ESA’s Messenger space mission benchmark, which is arguably one of the most difficult benchmarks available. The European Space Agency (ESA) created a continuous mid-scale black-box optimization benchmark which resembles an accurate model of NASA’s 2004 launched Messenger interplanetary space probe trajectory. By applying an evolutionary optimization algorithm (MXHPC/MIDACO) that relies on massive parallelization, it is demonstrated that it is possible to robustly solve this benchmark to a near global optimal solution within 1 hour on a computer cluster with 1000 CPU cores. This is a significant improvement over the previously published state-of-the-art results in 2017 where it was demonstrated for the first time that the Messenger benchmark could be solved in a fully automatic way and where it took about 12 h to achieve a near-optimal solution. The here presented results fortify the effectiveness of massively parallelized evolutionary computing for complex real-world problems which have been previously considered intractable.
Keywords
- Messenger mission
- Space trajectory
- Parallelization
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- 1.
Mingcheng Zuo (China Uni. of Geoscience) was able to refine this solution, so it rounds to an objective function value of f(x) = 1.958.
- 2.
From scratch means here that the lower bounds have been used for all test runs. Those test runs therefore aim at exploring the entire search space and are not refinements of previous found solutions.
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Schlueter, M., Wahib, M., Munetomo, M. (2021). New State-of-the-Art Results on ESA’s Messenger Space Mission Benchmark. In: Arabnia, H.R., et al. Advances in Parallel & Distributed Processing, and Applications. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-69984-0_48
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