Title
A novel hybrid sequential design strategy for global surrogate modeling of computer experimentsA novel hybrid sequential design strategy for global surrogate modeling of computer experiments
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Research group
Computational modelling en programming
Modeling Of Systems and Internet Communication (MOSAIC)
Publication type
article
Publication
Philadelphia, Pa,
Subject
Mathematics
Computer. Automation
Source (journal)
SIAM journal on scientific computing. - Philadelphia, Pa
Volume/pages
33(2011):4, p. 1948-1974
ISSN
1064-8275
ISI
000294293200022
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Many complex real-world systems can be accurately modeled by simulations. However, high-fidelity simulations may take hours or even days to compute. Because this can be impractical, a surrogate model is often used to approximate the dynamic behavior of the original simulator. This model can then be used as a cheap, drop-in replacement for the simulator. Because simulations can be very expensive, the data points, which are required to build the model, must be chosen as optimally as possible. Sequential design strategies offer a huge advantage over one-shot experimental designs because they can use information gathered from previous data points in order to determine the location of new data points. Each sequential design strategy must perform a trade-off between exploration and exploitation, where the former involves selecting data points in unexplored regions of the design space, while the latter suggests adding data points in regions which were previously identified to be interesting (for example, highly nonlinear regions). In this paper, a novel hybrid sequential design strategy is proposed which uses a Monte Carlobased approximation of a Voronoi tessellation for exploration and local linear approximations of the simulator for exploitation. The advantage of this method over other sequential design methods is that it is independent of the model type, and can therefore be used in heterogeneous modeling environments, where multiple model types are used at the same time. The new method is demonstrated on a number of test problems, showing that it is a robust, competitive, and efficient sequential design strategy.
E-info
https://repository.uantwerpen.be/docman/iruaauth/c5b172/984df6da13b.pdf
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