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

Gianluca Filippi, Massimiliano Vasile, Mariapia Marchi, Paolo Vercesi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.
LanguageEnglish
Title of host publicationIEEE world congress on computational intelligence
Place of PublicationPiscataway, N.J.
PublisherIEEE
Pages1-8
Number of pages8
StateAccepted/In press - 14 May 2018

Fingerprint

Aerospace engineering
Systems engineering
Large scale systems
Uncertainty

Keywords

  • space system engineering
  • evidence network models
  • Belief functions

Cite this

Filippi, G., Vasile, M., Marchi, M., & Vercesi, P. (Accepted/In press). Evidence-based robust optimisation of space systems with evidence network models. In IEEE world congress on computational intelligence (pp. 1-8). Piscataway, N.J.: IEEE.
Filippi, Gianluca ; Vasile, Massimiliano ; Marchi, Mariapia ; Vercesi, Paolo. / Evidence-based robust optimisation of space systems with evidence network models. IEEE world congress on computational intelligence. Piscataway, N.J. : IEEE, 2018. pp. 1-8
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Filippi, G, Vasile, M, Marchi, M & Vercesi, P 2018, Evidence-based robust optimisation of space systems with evidence network models. in IEEE world congress on computational intelligence. IEEE, Piscataway, N.J., pp. 1-8.

Evidence-based robust optimisation of space systems with evidence network models. / Filippi, Gianluca; Vasile, Massimiliano; Marchi, Mariapia; Vercesi, Paolo.

IEEE world congress on computational intelligence. Piscataway, N.J. : IEEE, 2018. p. 1-8.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Filippi G, Vasile M, Marchi M, Vercesi P. Evidence-based robust optimisation of space systems with evidence network models. In IEEE world congress on computational intelligence. Piscataway, N.J.: IEEE. 2018. p. 1-8.

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