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Using knowledge gradient in Bayesian optimization when searching for robust solutions
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Le, Hoai Phuong and Branke, Juergen (2022) Using knowledge gradient in Bayesian optimization when searching for robust solutions. Engineering Optimization . doi:10.1080/0305215X.2022.2145604 ISSN 0305-215X. (In Press)
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Official URL: https://doi.org/10.1080/0305215X.2022.2145604
Abstract
This article considers the use of Bayesian optimization to identify robust solutions, where robust means having a high expected performance given disturbances over the decision variables and independent noise in the output. A variant of the well-known knowledge gradient acquisition function is proposed specifically to search for robust solutions, with analytic expressions for uniformly and normally distributed disturbances. An empirical evaluation on a number of test problems demonstrates that the new acquisition function outperforms alternative approaches.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics Faculty of Social Sciences > Warwick Business School |
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| Library of Congress Subject Headings (LCSH): | Gaussian processes , Bayesian statistical decision theory, Reliability (Engineering) , Reliability (Engineering) -- Statistical methods, Robust optimization | |||||||||
| Journal or Publication Title: | Engineering Optimization | |||||||||
| Publisher: | Routledge | |||||||||
| ISSN: | 0305-215X | |||||||||
| Official Date: | 5 December 2022 | |||||||||
| Dates: |
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| DOI: | 10.1080/0305215X.2022.2145604 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | In Press | |||||||||
| Reuse Statement (publisher, data, author rights): | This is an Accepted Manuscript of an article published by Taylor & Francis in Engineering Optimization on 05/12/2022, available online: http://www.tandfonline.com/10.1080/0305215X.2022.2145604 | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 5 September 2022 | |||||||||
| Date of first compliant Open Access: | 14 December 2022 | |||||||||
| RIOXX Funder/Project Grant: |
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