Evidence-based robust optimisation of space systems with evidence network models

Filippi, Gianluca and Marchi, Mariapia and Vasile, Massimiliano and Vercesi, Paolo; (2018) Evidence-based robust optimisation of space systems with evidence network models. In: 2018 IEEE Congress on Evolutionary Computation. IEEE, BRA. ISBN 9781509060177

[thumbnail of Filippi-etal-IEEE-2018-Evidence-based-robust-optimisation-of-space-systems-with-evidence]
Preview
Text (Filippi-etal-IEEE-2018-Evidence-based-robust-optimisation-of-space-systems-with-evidence)
Filippi_etal_IEEE_2018_Evidence_based_robust_optimisation_of_space_systems_with_evidence.pdf
Accepted Author Manuscript

Download (468kB)| Preview

    Abstract

    The paper presents an approach to optimise complex systems in space systems engineering, accounting for epistemic uncertainty. Uncertainty is modelled with Dempster-Shafer theory of Evidence and the space system as a network of connected components. A constrained min-max problem is then solved, with a memetic algorithm, to deliver a robust design point. Starting from this robust design point a sequence of evolutionary optimisation steps are used to reconstruct an approximation of the Belief and Plausibility curves associated to a particular design solution. The constrained min-max approach and the evolutionary reconstruction of the Belief and Plausibility curves are tested on one realistic case study of space systems engineering.

    ORCID iDs

    Filippi, Gianluca, Marchi, Mariapia, Vasile, Massimiliano ORCID logoORCID: https://orcid.org/0000-0001-8302-6465 and Vercesi, Paolo;