Abstract
This investigation considers the optimization of multiple gravity assist capture trajectories in the Jupiter system combining the well known Differential Evolution algorithm with different classes of constraint handling techniques. The trajectories are designed to reach a desired target orbit around Jupiter with minimum fuel consumption while satisfying mission design constraints on maximum thrust level, maximum time of flight and minimum closest distance to the planet. The advanced constraints handling techniques are compared for different set of constraints on the challenging mission design problem. For each method the trade off between performance, efficiency and the structure of the feasible space is analyzed in light of the results obtained.
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Labroquère, J., Héritier, A., Riccardi, A., Izzo, D. (2014). Evolutionary Constrained Optimization for a Jupiter Capture. In: Bartz-Beielstein, T., Branke, J., Filipič, B., Smith, J. (eds) Parallel Problem Solving from Nature – PPSN XIII. PPSN 2014. Lecture Notes in Computer Science, vol 8672. Springer, Cham. https://doi.org/10.1007/978-3-319-10762-2_26
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DOI: https://doi.org/10.1007/978-3-319-10762-2_26
Publisher Name: Springer, Cham
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