whhxp / Platypus

A Free and Open Source Python Library for Multiobjective Optimization

Platypus

What is Platypus?

Platypus is a framework for evolutionary computing in Python with a focus on multiobjective evolutionary algorithms (MOEAs). It differs from existing optimization libraries, including PyGMO, Inspyred, DEAP, and Scipy, by providing optimization algorithms and analysis tools for multiobjective optimization. It currently supports NSGA-II, NSGA-III, MOEA/D, IBEA, Epsilon-MOEA, SPEA2, GDE3, OMOPSO, SMPSO, and Epsilon-NSGA-II. For more information, see our IPython Notebook or our online documentation.

Example

For example, optimizing a simple biobjective problem with a single real-valued decision variables is accomplished in Platypus with:

    from platypus import NSGAII, Problem, Real

    def schaffer(x):
        return [x[0]**2, (x[0]-2)**2]

    problem = Problem(1, 2)
    problem.types[:] = Real(-10, 10)
    problem.function = schaffer

    algorithm = NSGAII(problem)
    algorithm.run(10000)

Installation

To install the latest development version of Platypus using pip

    pip install git+https://github.com/whhxp/Platypus.git

To install the latest development version of Platypus, run the following commands:

    git clone https://github.com/whhxp/Platypus.git
    cd Platypus
    python setup.py install

License

Platypus is released under the GNU General Public License.