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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>.
| Version: |
0.6.2 |
| Imports: |
reticulate, nsga2R, lhs, nnet, stringr, randtoolbox, e1071, MASS, gtools, stats, utils, pracma |
| Suggests: |
testthat |
| Published: |
2020-08-31 |
| Author: |
Dani Irawan  [aut,
cre] |
| Maintainer: |
Dani Irawan <irawan_dani at yahoo.com> |
| BugReports: |
https://github.com/dots26/MaOEA/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/dots26/MaOEA |
| NeedsCompilation: |
no |
| SystemRequirements: |
Python 3.x with following modules: PyGMO, NumPy,
and cloudpickle |
| Citation: |
MaOEA citation info |
| Materials: |
README |
| In views: |
Optimization |
| CRAN checks: |
MaOEA results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=MaOEA
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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