Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.
|Author||Mickael Binois, Victor Picheny|
|Date of publication||2017-06-29 05:30:09 UTC|
|Maintainer||Mickael Binois <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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