Sequentially extending space-filling experimental designs by optimally permuting and stacking columns of the design matrix

J.D. Parker, T.W. Lucas and W.M. Carlyle

European Journal of Operational Research, 2024, vol. 319, issue 2, 600-610

Abstract: Researchers make available computationally expensive designs for computer experiments for widespread use by cataloging them and providing online links. This paper presents an algorithm that augments space-filling designs (SFDs) by optimally permuting and stacking columns of the design matrix to minimize the maximum absolute pairwise correlation among columns in the new extended design. The algorithm enables researchers to augment an SFD sequentially with batches of additional design points, which improves column orthogonality and adds more degrees of freedom for fitting metamodels. We show this method improves the correlation and space-filling properties of the resulting designs and allows us to extend some classes of designs to higher dimensions that are not easily obtainable. Moreover, the resulting extended designs compare well with many leading software-generated SFDs created from scratch in the extended design space.

Keywords: Simulation; Computer experiments; Design of experiments; Mixed integer programming; Sensitivity analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:319:y:2024:i:2:p:600-610

DOI: 10.1016/j.ejor.2024.06.020

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