A fast global optimizer based on improved CS-RBF and stochastic optimal algorithm

Siu Lau Ho, Shiyou Yang, Guangzheng Ni, H. C. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)


An improved compactly supported radial basis function is proposed as a response surface model in the study of computationally heavy design problems. A new interpolation formula is introduced to enhance the interpolation accuracy on boundary derivatives and the proposed response surface model is then combined with stochastic algorithms in the design of a fast global optimizer. Numerical results are reported to demonstrate the generality and the robustness of the proposed works.
Original languageEnglish
Pages (from-to)1175-1178
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number4
Publication statusPublished - 1 Apr 2006


  • Compact support
  • Global optimization
  • Inverse problem
  • Radial basis function
  • Response surface model

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Physics and Astronomy (miscellaneous)

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