The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

MaOEA Build Status

The goal of MaOEA is to facilitate easy hybridization of algorithms for many objective optimization. In the package, several algorithms are available: SMS-EMOA, NSGA-III, and MO-CMA-ES. Each of these algorithms can be accessed independently. Using the main function, the algorithms can be called for specific number of iterations. Alternatively, if the hybridization follows a more complex rule, users may prefer to call the algorithm directly in their optimization loop. This will call the algorithm (i.e., the offspring generation and selection scheme) for a single iteration.

The package uses PyGMO (https://esa.github.io/pagmo2/) to compute hypervolume and hypervolume contribution.

Installation

You can install the released version of MaOEA from CRAN with:

install.packages("MaOEA")

Please note that MaOEA requires the users to have installed Python (see https://www.python.org) and being able to use the PyGMO module. Installation instruction for PyGMO is available in https://esa.github.io/pagmo2/install.html. Users can also try to use the function provided in the package:

MaOEA::install_python_dependencies()

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.
Health stats visible at Monitor.