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http://hdl.handle.net/1942/39402| Title: | A BAYESIAN OPTIMIZATION ALGORITHM FOR CONSTRAINED PROBLEMS WITH HETEROSCEDASTIC NOISE | Authors: | AMINI, Sasan VAN NIEUWENHUYSE, Inneke |
Advisors: | Van Nieuwenhuyse, Inneke | Issue Date: | 2022 | Source: | Proceedings of the 20 Winter Simulation Conference, | Abstract: | In this research, we develop a Bayesian optimization algorithm to solve expensive constrained problems. We consider the presence of heteroscedastic noise in the evaluations, and propose an identification procedure that considers this uncertainty in recommending the final optimal solution(s). The primary experimental results show that the proposed algorithm is capable of finding a set of optimal (or near-optimal) solutions in the presence of noisy observations. | Document URI: | http://hdl.handle.net/1942/39402 | Category: | C2 | Type: | Conference Material |
| Appears in Collections: | Research publications |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| WSC-SasanAMINI(Poster).pdf Restricted Access | Conference material | 83.7 kB | Adobe PDF | View/Open Request a copy |
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