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

Gianluca Filippi; Massimiliano Vasile; Mariapia Marchi; Paolo Vercesi

doi:10.1109/CEC.2018.8477917

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 book

6 Citations (Scopus)

122 Downloads (Pure)

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.

Original language	English
Title of host publication	2018 IEEE Congress on Evolutionary Computation
Place of Publication	Piscataway, N.J.
Publisher	IEEE
Pages	1-8
Number of pages	8
ISBN (Print)	9781509060177
DOIs	https://doi.org/10.1109/CEC.2018.8477917
Publication status	Published - 4 Oct 2018
Event	2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brazil Duration: 8 Jul 2018 → 13 Jul 2018

Conference

Conference	2018 IEEE Congress on Evolutionary Computation, CEC 2018
Country	Brazil
City	Rio de Janeiro
Period	8/07/18 → 13/07/18

Keywords

space system engineering
evidence network models
Belief functions

Access to Document

10.1109/CEC.2018.8477917

Filippi-etal-IEEE-2018-Evidence-based-robust-optimisation-of-space-systems-with-evidenceAccepted author manuscript, 464 KB

http://www.ecomp.poli.br/~wcci2018/

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Cite this

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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.",

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