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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.
Getting started
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Package details |
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| Author | Mickael Binois, Victor Picheny |
| Maintainer | Mickael Binois <mickael.binois@inria.fr> |
| License | GPL-3 |
| Version | 1.1.8 |
| URL | https://github.com/mbinois/GPareto |
| Package repository | View on CRAN |
| Installation |
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