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

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

doi:10.1109/TMAG.2006.871429

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

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

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

4 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	1175-1178
Number of pages	4
Journal	IEEE Transactions on Magnetics
Volume	42
Issue number	4
DOIs	https://doi.org/10.1109/TMAG.2006.871429
Publication status	Published - 1 Apr 2006

Keywords

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

ASJC Scopus subject areas

Electrical and Electronic Engineering
Physics and Astronomy (miscellaneous)

More information

10.1109/TMAG.2006.871429

http://hdl.handle.net/10397/893

Cite this

@article{fbb5be980aeb434f8f9b837cd548cfa3,

title = "A fast global optimizer based on improved CS-RBF and stochastic optimal algorithm",

abstract = "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.",

keywords = "Compact support, Global optimization, Inverse problem, Radial basis function, Response surface model",

author = "Ho, {Siu Lau} and Shiyou Yang and Guangzheng Ni and Wong, {H. C.}",

year = "2006",

month = apr,

day = "1",

doi = "10.1109/TMAG.2006.871429",

language = "English",

volume = "42",

pages = "1175--1178",

journal = "IEEE Transactions on Magnetics",

issn = "0018-9464",

publisher = "IEEE",

number = "4",

}

TY - JOUR

T1 - A fast global optimizer based on improved CS-RBF and stochastic optimal algorithm

AU - Ho, Siu Lau

AU - Yang, Shiyou

AU - Ni, Guangzheng

AU - Wong, H. C.

PY - 2006/4/1

Y1 - 2006/4/1

N2 - 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.

AB - 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.

KW - Compact support

KW - Global optimization

KW - Inverse problem

KW - Radial basis function

KW - Response surface model

UR - http://www.scopus.com/inward/record.url?scp=33645140772&partnerID=8YFLogxK

U2 - 10.1109/TMAG.2006.871429

DO - 10.1109/TMAG.2006.871429

M3 - Journal article

SN - 0018-9464

VL - 42

SP - 1175

EP - 1178

JO - IEEE Transactions on Magnetics

JF - IEEE Transactions on Magnetics

IS - 4

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

More information

Other files and links

Fingerprint

Cite this