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>.">

miesmuschel: Mixed Integer Evolution Strategies (original) (raw)

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: 0.0.4-2
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: 2024-07-09
DOI: 10.32614/CRAN.package.miesmuschel
Author: Martin Binder [aut, cre], Lennart Schneider ORCID iD [ctb], Susanne Dandl ORCID iD [ctb], Andreas Hofheinz [ctb]
Maintainer: Martin Binder <mlr.developer at mb706.com>
BugReports: https://github.com/mlr-org/miesmuschel/issues
License: MIT + file
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 formhttps://CRAN.R-project.org/package=miesmuschelto link to this page.