Package: MaOEA 0.7.1

MaOEA: Many Objective Evolutionary Algorithm

A set of evolutionary algorithms to solve many-objective optimization. Hybridization between the algorithms are also facilitated. Available algorithms are: 'SMS-EMOA' <doi:10.1016/j.ejor.2006.08.008> 'NSGA-III' <doi:10.1109/TEVC.2013.2281535> 'MO-CMA-ES' <doi:10.1145/1830483.1830573> The following many-objective benchmark problems are also provided: 'DTLZ1'-'DTLZ4' from Deb, et al. (2001) <doi:10.1007/1-84628-137-7_6> and 'WFG4'-'WFG9' from Huband, et al. (2005) <doi:10.1109/TEVC.2005.861417>.

Authors:Dani Irawan [aut, cre]

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Peer review:

Bug tracker:https://github.com/dots26/maoea/issues

On CRAN:

36 exports 6 stars 1.59 score 31 dependencies 2 mentions 233 downloads

Last updated 2 years agofrom:ad62161655. Checks:OK: 1 ERROR: 6. Indexed: yes.

Exports:AdaptiveNormalizationcmaes_gencompute_R2HVcompute_R2HVCcompute_R2mtchcreateWeightscreateWeightsSobolDTLZ1DTLZ2DTLZ3DTLZ4EvaluateIndividualEvaluatePopulationGetHVContributionGetHypervolumeGetIGDGetLeastContributionGetLeastContributorInitializePopulationLHSinstall_python_dependenciesload_python_dependenciesMOCMAESNormalizeNSGA3optimMaOEASMOCMAESSMSEMOAWFG1WFG2WFG3WFG4WFG5WFG6WFG7WFG8WFG9

Dependencies:classclie1071gluegtoolsherejsonlitelatticelhslifecyclemagrittrMASSMatrixmconnetnsga2RpngpracmaproxyrandtoolboxrappdirsRcppRcppTOMLreticulaterlangrngWELLrprojrootstringistringrvctrswithr