Liu, C-Y, Liu, D-Z, Mao, X orcid.org/0000-0002-9004-2081 et al. (1 more author) (2018) Extended Multipoint Approximation Method. In: DEStech Transactions on Computer Science and Engineering. 2nd International Conference on Applied Mathematics, Simulation and Modelling (AMSM 2017), 06-07 Aug 2017, Phuket, Thailand. DEStech Publications, Inc. , pp. 219-225. ISBN 978-1-60595-480-6
Abstract
Stemming from polynomial metamodels, multipoint approximation method (MAM) and moving least square method (MLSM) focus on the development of metamodels for the objective and constraint functions in solving a mid-range optimization problem with a trust region. Although both of these methods could solve problems successfully, there is still some room for improvement on the computational effort and search capability. To address this problem, the extended multipoint approximation method is proposed to seek the optimal solution in this paper. The developed method assimilating the advantage of Taylor’s expansion used in MLSM demonstrates its superiority over other methods in terms of the computational efficiency and accuracy by some well-established benchmark problems.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 by DEStech Publications, Inc. This article appeared in its original form in DEStech Transactions on Computer Science and Engineering, 2017. Lancaster, PA: DEStech Publications, Inc. This author produced version uploaded with permission from the publisher. |
Keywords: | Metamodel; Multipoint approximation method; Moving least square method; Taylor's expansion |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Sep 2017 14:07 |
Last Modified: | 06 Jul 2018 10:18 |
Status: | Published |
Publisher: | DEStech Publications, Inc. |
Identification Number: | 10.12783/dtetr/amsm2017/14847 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:120907 |