Multi-objective optimisation under uncertainty with unscented temporal finite elements

Ricciardi, Lorenzo Angelo and Maddock, Christie and Vasile, Massimiliano; Greiner, David and Gaspar-Cunha, Antonio and Hernández-Sosa, Daniel and Minisci, Edmondo and Zamuda, Aleš, eds. (2022) Multi-objective optimisation under uncertainty with unscented temporal finite elements. In: Evolutionary Algorithms in Engineering Design Optimization. MDPI Multidisciplinary Digital Publishing Institute, Basel, pp. 187-208. ISBN 9783036527154 (https://doi.org/10.3390/math9233010)

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Abstract

This paper presents a novel method for multi-objective optimisation under uncertainty developed to study a range of mission trade-offs, and the impact of uncertainties on the evaluation of launch system mission designs. A memetic multi-objective optimisation algorithm, named MODHOC, which combines the Direct Finite Elements in Time transcription method with Multi Agent Collaborative Search, is extended to account for model uncertainties. An Unscented Transformation is used to capture the first two statistical moments of the quantities of interest. A quantification model of the uncertainty was developed for the atmospheric model parameters. An optimisation under uncertainty was run for the design of descent trajectories for a spaceplane-based two-stage launch system.

ORCID iDs

Ricciardi, Lorenzo Angelo ORCID: https://orcid.org/0000-0002-0895-7961

Maddock, Christie ORCID: https://orcid.org/0000-0003-1079-4863

Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465

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• Item metadata

  Item type:	Book Section
  ID code:	80035
  Dates:	Date Event 1 March 2022 Published 24 November 2021 Published Online 16 November 2021 Accepted
  Notes:	The book in which this chapter has been published is a reprint of articles from the Special Issue published online in the open access journal Mathematics (ISSN 2227-7390) (available at: https://www.mdpi.com/journal/mathematics/special issues/Evolutionary Algorithms Engineering Design Optimization)
  Subjects:	Technology > Motor vehicles. Aeronautics. Astronautics
  Department:	Faculty of Engineering > Mechanical and Aerospace Engineering Strategic Research Themes > Ocean, Air and Space
  Depositing user:	Pure Administrator
  Date deposited:	31 Mar 2022 16:22
  Last modified:	15 Dec 2024 01:10
  URI:	https://strathprints.strath.ac.uk/id/eprint/80035