Extended Multipoint Approximation Method

Cheng-yang Liu, Dian-zi Liu, Xiao-an Mao, Xue Zhou

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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 publicationDEStech Transactions on Engineering and Technology Research
PublisherDEStech Publications, Inc.
Pages219-225
DOIs
Publication statusPublished - 6 Aug 2017

Publication series

NameDEStech Transactions on Engineering and Technology Research
PublisherDEStech Publications, Inc
ISSN (Electronic)2475-885X

Keywords

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

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