Package: GPareto 1.1.9

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.

Authors:Mickael Binois, Victor Picheny

GPareto_1.1.9.tar.gz
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GPareto.pdf |GPareto.html✨
GPareto/json (API)
NEWS

# Install 'GPareto' in R:
install.packages('GPareto', repos = c('https://mbinois.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mbinois/gpareto/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

6.44 score 16 stars 1 packages 38 scripts 938 downloads 36 exports 54 dependencies

Last updated 10 months agofrom:fe43d0dd5d. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-win-x86_64OKNov 02 2024
R-4.5-linux-x86_64OKNov 02 2024
R-4.4-win-x86_64OKNov 02 2024
R-4.4-mac-x86_64OKNov 02 2024
R-4.4-mac-aarch64OKNov 02 2024
R-4.3-win-x86_64OKNov 02 2024
R-4.3-mac-x86_64OKNov 02 2024
R-4.3-mac-aarch64OKNov 02 2024

Exports:checkPredictCPFcrit_EHIcrit_EMIcrit_optimizercrit_qEHIcrit_SMScrit_SURDTLZ1DTLZ2DTLZ3DTLZ7easyGParetoptimfastfungetDesignGParetoptimintegration_design_optimMOP2MOP3nonDomSetOKA1P1P2ParetoSetDensityplot_uncertaintyplotGParetoplotParetoEmpplotParetoGridplotSymDevFunplotSymDifRNPpredict_kmsZDT1ZDT2ZDT3ZDT4ZDT6

Dependencies:anMCbase64encbslibcachemcliDiceDesignDiceKrigingdigestemoaevaluatefastmapFNNfontawesomefsgluehighrhtmltoolshtmlwidgetsjquerylibjsonlitekernlabKernSmoothknitrKrigInvkslatticelifecyclemagrittrMASSMatrixmclustmemoisemgcvmimemulticoolmvtnormnlmepbivnormpracmapsoR6randtoolboxrappdirsRcppRcppArmadillorgenoudrglrlangrmarkdownrngWELLsasstinytexxfunyaml

a guide to the GPareto package

Rendered fromGPareto_vignette.Rnwusingknitr::knitron Nov 02 2024.

Last update: 2024-01-26
Started: 2018-02-04

Readme and manuals

Help Manual

Help pageTopics
Package GParetoGPareto-package GPareto
Prevention of numerical instability for a new observationcheckPredict
Conditional Pareto Front simulationsCPF
Expected Hypervolume Improvement with m objectivescrit_EHI
Expected Maximin Improvement with m objectivescrit_EMI
Maximization of multiobjective infill criterioncrit_optimizer
Batch Expected Hypervolume Improvement with m objectivescrit_qEHI
Analytical expression of the SMS-EGO criterion with m>1 objectivescrit_SMS
Analytical expression of the SUR criterion for two or three objectives.crit_SUR
EGO algorithm for multiobjective optimizationeasyGParetoptim
Fast-to-evaluate function wrapperfastfun
Get design corresponding to an objective targetgetDesign
Sequential multi-objective Expected Improvement maximization and model re-estimation, with a number of iterations fixed in advance by the userGParetoptim
Function to build integration points (for the SUR criterion)integration_design_optim
Non-dominated points with respect to a referencenonDomSet
Estimation of Pareto set densityParetoSetDensity
Plot uncertaintyplot_uncertainty
Plot multi-objective optimization results and post-processingplotGPareto
Pareto front visualizationplotParetoEmp
Visualisation of Pareto front and setplotParetoGrid
Display the Symmetric Deviation FunctionplotSymDevFun
Symmetrical difference of RNP setsplotSymDifRNP
Predict function for list of 'km' models.predict_kms
Test functions of xDTLZ1 DTLZ2 DTLZ3 DTLZ7 MOP2 MOP3 OKA1 P1 P2 ZDT1 ZDT2 ZDT3 ZDT4 ZDT6