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http://hdl.handle.net/1942/40077
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DC Field | Value | Language |
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dc.contributor.author | MORALES HERNANDEZ, Alejandro | - |
dc.contributor.author | VAN NIEUWENHUYSE, Inneke | - |
dc.contributor.author | ROJAS GONZALEZ, Sebastian | - |
dc.contributor.author | JORDENS, Jeroen | - |
dc.contributor.author | Witters, Maarten | - |
dc.contributor.author | Van Doninck, Bart | - |
dc.date.accessioned | 2023-05-10T10:06:10Z | - |
dc.date.available | 2023-05-10T10:06:10Z | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-03-21T09:14:48Z | - |
dc.identifier.citation | Bernabe , Dorronsoro; Francisco, Chicano; Danoy, Gregoire; Talbi, El-Ghazali (Ed.). Optimization and Learning - 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings, | - |
dc.identifier.isbn | 978-3-031-34019-2 | - |
dc.identifier.issn | 1865-0929 | - |
dc.identifier.uri | http://hdl.handle.net/1942/40077 | - |
dc.description.abstract | Finding the optimal process parameters for an adhesive bonding process is challenging: the optimization is inherently multi-objective (aiming to maximize break strength while minimizing cost), constrained (the process should not result in any visual damage to the materials, and stress tests should not result in adhesive failures), and uncertain (mea-suring the same process parameters several times lead to different break strength). Real-life physical experiments in the lab are expensive to perform (∼6 hours of experimentation and subsequent production costs); traditional evolutionary approaches are then ill-suited to solve the problem , due to the prohibitive amount of experiments required for evaluation. In this research, we successfully applied specific machine learning techniques (Gaussian Process Regression and Logistic Regression) to emulate the objective and constraint functions based on a limited amount of experimental data. The techniques are embedded in a Bayesian optimization algorithm, which succeeds in detecting Pareto-optimal process settings in a highly efficient way (i.e., requiring a limited number of experiments). | - |
dc.description.sponsorship | This research was supported by the FLAIR Program and by the Research Foundation Flanders (FWO Grant 1216021N). | - |
dc.language.iso | en | - |
dc.relation.ispartofseries | Communications in Computer and Information Science | - |
dc.rights | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 | - |
dc.subject.other | multi-objective optimization | - |
dc.subject.other | constrained optimization | - |
dc.subject.other | machine learning | - |
dc.subject.other | adhesive bonding | - |
dc.title | Multi-objective optimization of adhesive bonding process in constrained and noisy settings | - |
dc.type | Proceedings Paper | - |
dc.relation.edition | 6 | - |
local.bibliographicCitation.authors | Bernabe , Dorronsoro | - |
local.bibliographicCitation.authors | Francisco, Chicano | - |
local.bibliographicCitation.authors | Danoy, Gregoire | - |
local.bibliographicCitation.authors | Talbi, El-Ghazali | - |
local.bibliographicCitation.conferencedate | May 3 - 5 | - |
local.bibliographicCitation.conferencename | International Conference on Optimization and Learning | - |
local.bibliographicCitation.conferenceplace | Malaga | - |
local.format.pages | 417 | - |
local.bibliographicCitation.jcat | C1 | - |
local.type.refereed | Non-Refereed | - |
local.type.specified | Proceedings Paper | - |
local.relation.ispartofseriesnr | 1824 | - |
local.bibliographicCitation.status | In press | - |
dc.identifier.url | https://link.springer.com/conference/ola | - |
dc.identifier.eissn | 1865-0937 | - |
local.provider.type | - | |
local.bibliographicCitation.btitle | Optimization and Learning - 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings | - |
local.uhasselt.international | no | - |
item.fulltext | With Fulltext | - |
item.fullcitation | MORALES HERNANDEZ, Alejandro; VAN NIEUWENHUYSE, Inneke; ROJAS GONZALEZ, Sebastian; JORDENS, Jeroen; Witters, Maarten & Van Doninck, Bart (2023) Multi-objective optimization of adhesive bonding process in constrained and noisy settings. In: Bernabe , Dorronsoro; Francisco, Chicano; Danoy, Gregoire; Talbi, El-Ghazali (Ed.). Optimization and Learning - 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings,. | - |
item.accessRights | Restricted Access | - |
item.contributor | MORALES HERNANDEZ, Alejandro | - |
item.contributor | VAN NIEUWENHUYSE, Inneke | - |
item.contributor | ROJAS GONZALEZ, Sebastian | - |
item.contributor | JORDENS, Jeroen | - |
item.contributor | Witters, Maarten | - |
item.contributor | Van Doninck, Bart | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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JMLab_OLA_2023.pdf Restricted Access | Early view | 1.68 MB | Adobe PDF | View/Open Request a copy |
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