Abstract
| 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 | |
| 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 |
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Keywords
- space system engineering
- evidence network models
- Belief functions
Cite this
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Evidence-based robust optimisation of space systems with evidence network models. / Filippi, Gianluca; Vasile, Massimiliano; Marchi, Mariapia; Vercesi, Paolo.
2018 IEEE Congress on Evolutionary Computation. Piscataway, N.J. : IEEE, 2018. p. 1-8.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Evidence-based robust optimisation of space systems with evidence network models
AU - Filippi, Gianluca
AU - Vasile, Massimiliano
AU - Marchi, Mariapia
AU - Vercesi, Paolo
PY - 2018/10/4
Y1 - 2018/10/4
N2 - 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.
AB - 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.
KW - space system engineering
KW - evidence network models
KW - Belief functions
UR - http://www.ecomp.poli.br/~wcci2018/
U2 - 10.1109/CEC.2018.8477917
DO - 10.1109/CEC.2018.8477917
M3 - Conference contribution book
AN - SCOPUS:85056274179
SN - 9781509060177
SP - 1
EP - 8
BT - 2018 IEEE Congress on Evolutionary Computation
PB - IEEE
CY - Piscataway, N.J.
ER -