Please use this identifier to cite or link to this item:
https://doi.org/10.1016/B978-0-12-818597-1.50016-3
DC Field | Value | |
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dc.title | Two Stage Surrogate Assisted Framework For Box-Constrained Global Optimisation | |
dc.contributor.author | SUSHANT SUHAS GARUD | |
dc.contributor.author | Nivethitha Mariappan | |
dc.contributor.author | KARIMI,IFTEKHAR ABUBAKAR | |
dc.date.accessioned | 2020-06-05T00:37:45Z | |
dc.date.available | 2020-06-05T00:37:45Z | |
dc.date.issued | 2019-07-31 | |
dc.identifier.citation | SUSHANT SUHAS GARUD, Nivethitha Mariappan, KARIMI,IFTEKHAR ABUBAKAR (2019-07-31). Two Stage Surrogate Assisted Framework For Box-Constrained Global Optimisation. Computer Aided Chemical Engineering 47 : 95-100. ScholarBank@NUS Repository. https://doi.org/10.1016/B978-0-12-818597-1.50016-3 | |
dc.identifier.issn | 15707946 | |
dc.identifier.uri | https://scholarbank.nus.edu.sg/handle/10635/169292 | |
dc.description.abstract | In this work, we propose a novel black-box optimisation approach, which blends the concepts of “trust-region” and “adaptive sample placement” to obtain the global minimum for limited computational budget while escaping local optima traps, if any. This is translated into mathematical formulation by iteratively constructing sub-regions based on Delaunay triangulation and adding new sample points sequentially to the selected sub-regions via placement optimisation that balances between domain exploration and exploitation. Our numerical evaluation shows that the proposed approach successfully locates the global minima and outperforms four black-box optimisation algorithms from the literature for six test problems. Overall, this work develops a generalised surrogate-assisted framework for black-box optimisation that holds much promise in solving design as well as operational problems. | |
dc.description.uri | https://doi.org/10.1016/B978-0-12-818597-1.50016-3 | |
dc.language.iso | en | |
dc.publisher | Elsevier | |
dc.type | Conference Paper | |
dc.contributor.department | CHEMICAL & BIOMOLECULAR ENGINEERING | |
dc.description.doi | 10.1016/B978-0-12-818597-1.50016-3 | |
dc.description.sourcetitle | Computer Aided Chemical Engineering | |
dc.description.volume | 47 | |
dc.description.page | 95-100 | |
dc.published.state | Published | |
dc.grant.id | NRF2017EWTEP003-020 | |
dc.grant.fundingagency | National Research Foundation | |
Appears in Collections: | Staff Publications Elements |
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FOCAPD-Manuscript_20181205.pdf | 284.77 kB | Adobe PDF | CLOSED | Post-print |
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