You can find the detailed documentation here: https://pymoo.org
We are currently working on a paper about pymoo. Meanwhile, if you have used our framework for research purposes, please cite us with:
@misc{pymoo, author = {Julian Blank and Kalyanmoy Deb}, title = {pymoo - {Multi-objective Optimization in Python}}, howpublished = {https://pymoo.org} }
First, make sure you have a Python 3 environment installed. We recommend miniconda3 or anaconda3.
The official release is always available at PyPi:
pip install Cython>=0.29 numpy>=1.15 pymoo
For the current developer version:
git clone https://github.com/msu-coinlab/pymoo
cd pymoo
pip install .
Since for speedup some of the modules are also available compiled you can double check if the compilation worked. When executing the command be sure not already being in the local pymoo directory because otherwise not the in site-packages installed version will be used.
python -c "from pymoo.cython.function_loader import is_compiled;print('Compiled Extensions: ', is_compiled())"
We refer here to our documentation for all the details. However, for instance executing NSGA2:
import numpy as np
from pymoo.optimize import minimize
from pymoo.util import plotting
from pymop.factory import get_problem
# create the optimization problem
problem = get_problem("zdt1")
pf = problem.pareto_front()
res = minimize(problem,
method='nsga2',
method_args={'pop_size': 100},
termination=('n_gen', 200),
pf=pf,
save_history=True,
disp=True)
plot = True
if plot:
plotting.plot(pf, res.F, labels=["Pareto-front", "F"])
# set true if you want to save a video
animate = False
if animate:
from pymoo.util.plotting import animate as func_animtate
H = np.concatenate([e.pop.get("F")[None, :] for e in res.history], axis=0)
func_animtate('%s.mp4' % problem.name(), H, problem)
Feel free to contact me if you have any question: