GPareto (1.0.2)

Gaussian Processes for Pareto Front Estimation and Optimization.

Gaussian process regression models, a.k.a. kriging models, are applied to global multiobjective optimization of black-box functions. Multiobjective 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, knitr
Reverse suggests: DiceOptim

Released almost 3 years ago.