swMATH ID: 28711
Software Authors: Mickaël Binois; Victor Picheny
Description: R package GPareto: 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.
Homepage: https://cran.r-project.org/web/packages/GPareto/index.html
Source Code:  https://github.com/cran/GPareto
Dependencies: R
Keywords: kriging; Pareto front; efficient global optimization; uncertainty quantification; Journal of Statistical Software; R; R package
Related Software: ParEGO; EGO; MOEA/D; R; HypE; PESC; DiceOptim; DiceEval; KrigInv; DiceDesign; rgenoud; DiceKriging; Hyperopt; nsga2R; Matlab; goalprog; mopsocd; mco; STK; NLopt
Cited in: 4 Documents

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