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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.
|Title of host publication||2018 IEEE Congress on Evolutionary Computation|
|Place of Publication||Piscataway, N.J.|
|Number of pages||8|
|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||2018 IEEE Congress on Evolutionary Computation, CEC 2018|
|City||Rio de Janeiro|
|Period||8/07/18 → 13/07/18|
- space system engineering
- evidence network models
- Belief functions
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