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 logoORCID: https://orcid.org/0000-0002-0895-7961, Maddock, Christie ORCID logoORCID: https://orcid.org/0000-0003-1079-4863 and Vasile, Massimiliano ORCID logoORCID: https://orcid.org/0000-0001-8302-6465; Greiner, David, Gaspar-Cunha, Antonio, Hernández-Sosa, Daniel, Minisci, Edmondo and Zamuda, Aleš
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