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Optimization with missing data

Forrester, Alexander I.J., Sobester, Andras and Keane, Andy J. (2006) Optimization with missing data Proceedings of the Royal Society of London A, 462, (2067), pp. 935-945. (doi:10.1098/rspa.2005.1608).

Record type: Article


Engineering optimization relies routinely on deterministic computer based design evaluations, typically comprising geometry creation, mesh generation and numerical simulation. Simple optimization routines tend to stall and require user intervention if a failure occurs at any of these stages. This motivated us to develop an optimization strategy based on surrogate modelling, which penalizes the likely failure regions of the design space without prior knowledge of their locations. A Gaussian process based design improvement expectation measure guides the search towards the feasible global optimum.

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Published date: 2006
Keywords: global optimization, imputation, kriging


Local EPrints ID: 23505
ISSN: 1364-5021
PURE UUID: a6a1d160-5888-4d5e-90c2-9c0a3eb8e529
ORCID for Andras Sobester: ORCID iD

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Date deposited: 13 Mar 2006
Last modified: 17 Jul 2017 16:17

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