GPareto (

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Gaussian Processes for Pareto Front Estimation and Optimization.

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.

Maintainer: Mickael Binois
Author(s): Mickael Binois, Victor Picheny

License: GPL-3

Uses: DiceDesign, DiceKriging, emoa, KrigInv, ks, MASS, pbivnorm, pso, randtoolbox, Rcpp, rgenoud, rgl, knitr
Reverse suggests: DiceOptim

Released 2 months ago.

9 previous versions



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