An efficient algorithm for constructing optimal design of computer experiments

Ruichen Jin, Wei Chen*, Agus Sudjianto

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

36 Scopus citations

Abstract

Metamodeling approach has been widely used due to the high computational cost of using high-fidelity simulations in engineering design. The accuracy of metamodels is directly related to the experimental designs used. Optimal experimental designs have been shown to have good "space filling" and projective properties. However, the high cost in constructing them limits their use. In this paper, a new algorithm for constructing optimal experimental designs is developed. There are two major developments involved in this work. One is on developing an efficient global optimal search algorithm, named as enhanced stochastic evolutionary (ESE) algorithm. The other is on developing efficient algorithms for evaluating optimally criteria. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time, the number of exchanges needed for generating new designs, and the achieved optimality criteria. The algorithm is also very flexible to construct various classes of optimal designs to retain certain structural properties.

Original languageEnglish (US)
Pages545-554
Number of pages10
DOIs
StatePublished - 2003
Event2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Chicago, IL, United States
Duration: Sep 2 2003Sep 6 2003

Other

Other2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CountryUnited States
CityChicago, IL
Period9/2/039/6/03

Keywords

  • Computer experiments
  • Metamodeling
  • Optimal design
  • Stochastic evolutionary algorithm

ASJC Scopus subject areas

  • Engineering(all)

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