Evolutionary black box optimization algorithms building on the 'bbotk' package. 'miesmuschel' offers both ready-to-use optimization algorithms, as well as their fundamental building blocks that can be used to manually construct specialized optimization loops. The Mixed Integer Evolution Strategies as described by Li et al. (2013) <doi:10.1162/EVCO_a_00059> can be implemented, as well as the multi-objective optimization algorithms NSGA-II by Deb, Pratap, Agarwal, and Meyarivan (2002) <doi:10.1109/4235.996017>.
Version: 0.0.4-3 Depends: paradox (≥ 0.7.1) Imports: mlr3misc (≥ 0.5.0), checkmate (≥ 1.9.0), R6, bbotk (≥ 0.3.0.900), data.table, matrixStats, lgr Suggests: tinytest, mlr3tuning, mlr3, mlr3learners, ranger, xgboost, rpart Published: 2025-03-19 DOI: 10.32614/CRAN.package.miesmuschel Author: Martin Binder [aut, cre], Lennart Schneider [ctb], Susanne Dandl [ctb], Andreas Hofheinz [ctb] Maintainer: Martin Binder <mlr.developer at mb706.com> BugReports: https://github.com/mlr-org/miesmuschel/issues License: MIT + file LICENSE URL: https://github.com/mlr-org/miesmuschel NeedsCompilation: no Materials: README, NEWS CRAN checks: miesmuschel results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=miesmuschel to link to this page.
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