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.
GPareto: Gaussian Processes for Pareto Front Estimation and Optimization
This R package provides tools for multi-objective optimization of expensive black-box functions along with estimation of Pareto fronts.
For the stable version: http://cran.r-project.org/package=GPareto
This the development version, contributions are welcomed.