Global Optimization of Deceptive Functions With Sparse Sampling

نویسندگان

  • Alexander I.J. Forrester
  • Donald R. Jones
چکیده

This paper introduces a new method of calculating the expected improvement infill criterion, which does not rely on accurate model parameter estimation. The parameter estimation is embedded within the search of the infill criterion, wherein parameter changes are assessed using likelihood ratio tests. Unlike the traditional expected improvement, a new formulation we present cannot be ‘fooled’ by unlucky sampling or deceptive functions. The new method is introduced both mathematically and illustratively using a one-variable test function. It is then shown to outperform traditional expected improvement when optimizing the geometry of a passive vibration isolating truss.

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تاریخ انتشار 2008