Parallel surrogate-assisted optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO
Abstract
Surrogate-based optimization is widely used to deal with long-running black-box simulation-based objective functions. Actually, the use of a surrogate model such as Kriging or Artificial Neural Network allows to reduce the number of calls to the CPU time-intensive simulator. Bayesian optimization uses the ability of surrogates to provide useful information to help guiding effectively the optimization process. In this paper, the Efficient Global...
Paper Details
Title
Parallel surrogate-assisted optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO
Published Date
Sep 1, 2020
Volume
57
Pages
100717 - 100717
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