Discrete particle swarm optimization for constructing uniform design on irregular regions

Ray Bing Chen, Yen Wen Hsu, Ying Hung, Weichung Wang

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Central composite discrepancy (CCD) has been proposed to measure the uniformity of a design over irregular experimental region. However, how CCD-based optimal uniform designs can be efficiently computed remains a challenge. Focusing on this issues, we proposed a particle swarm optimization-based algorithm to efficiently find optimal uniform designs with respect to the CCD criterion. Parallel computation techniques based on state-of-the-art graphic processing unit (GPU) are employed to accelerate the computations. Several two- to five-dimensional benchmark problems are used to illustrate the advantages of the proposed algorithms. By solving a real application in data center thermal management, we further demonstrate that the proposed algorithm can be extended to incorporate desirable space-filling properties, such as the non-collapsing property.

Original languageEnglish (US)
Pages (from-to)282-297
Number of pages16
JournalComputational Statistics and Data Analysis
Volume72
DOIs
StatePublished - Apr 1 2014

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

Keywords

  • Central composite discrepancy
  • Graphic processing unit
  • Non-collapsing
  • Parallel computing

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