Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package

Picheny, Victor; Ginsbourger, David (2014). Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. Computational statistics & data analysis, 71, pp. 1035-1053. Elsevier 10.1016/j.csda.2013.03.018

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Kriging-based optimization relying on noisy evaluations of complex systems has recently motivated contributions from various research communities. Five strategies have been implemented in the DiceOptim package. The corresponding functions constitute a user-friendly tool for solving expensive noisy optimization problems in a sequential framework, while offering some flexibility for advanced users. Besides, the implementation is done in a unified environment, making this package a useful device for studying the relative performances of existing approaches depending on the experimental setup. An overview of the package structure and interface is provided, as well as a description of the strategies and some insight about the implementation challenges and the proposed solutions. The strategies are compared to some existing optimization packages on analytical test functions and show promising performances.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Mathematics and Statistics > Institute of Mathematical Statistics and Actuarial Science

UniBE Contributor:

Ginsbourger, David

Subjects:

500 Science > 510 Mathematics

ISSN:

0167-9473

Publisher:

Elsevier

Language:

English

Submitter:

Lutz Dümbgen

Date Deposited:

01 Apr 2014 02:56

Last Modified:

21 Jun 2021 14:30

Publisher DOI:

10.1016/j.csda.2013.03.018

BORIS DOI:

10.7892/boris.41533

URI:

https://boris.unibe.ch/id/eprint/41533

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