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 journalArticlepeer-review

514 Scopus citations


The long computational time required in constructing optimal designs for computer experiments has limited their uses in practice. 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 methods for evaluating optimality criteria. The proposed algorithm is compared to existing techniques and 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 desired structural properties.

Original languageEnglish (US)
Pages (from-to)268-287
Number of pages20
JournalJournal of Statistical Planning and Inference
Issue number1
StatePublished - Sep 1 2005


  • Computer experiments
  • Optimal design
  • Stochastic evolutionary algorithm

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics


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