Extended Multipoint Approximation Method. In: DEStech Transactions on Computer Science and Engineering.

Cheng-Yang Liu, Dianzi Liu, Xiaoan Mao, Xue Zhou

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    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.
    Original languageEnglish
    Title of host publication2nd International Conference on Applied Mathematics, Simulation and Modelling
    Place of PublicationPhuket, Thailand
    PublisherDestech Publications Inc.
    Pages219-225
    Number of pages6
    ISBN (Print)978-1-60595-480-6
    DOIs
    Publication statusPublished - 2018
    Event2nd International Conference on Applied Mathematics, Simulation and Modelling - Phuket, Thailand
    Duration: 6 Aug 20177 Aug 2017

    Conference

    Conference2nd International Conference on Applied Mathematics, Simulation and Modelling
    Abbreviated titleAMSM 2017
    Country/TerritoryThailand
    CityPhuket
    Period6/08/177/08/17

    Keywords

    • Metamodel
    • Multipoint approximation method
    • Moving least square method
    • Taylor’s expansion

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