Version: 0.6.0

# DF: Benchmark Problems for CEC2018 Competition on Dynamic Multiobjective Optimisation¶

The problem suite is implemented based on [44].

## DF1¶

[1]:

import numpy as np

from pymoo.problems.dynamic.df import DF1
from pymoo.visualization.scatter import Scatter

plot = Scatter()

for t in np.linspace(0, 10.0, 100):
problem = DF1(time=t)

plot.show()

[1]:

<pymoo.visualization.scatter.Scatter at 0x7f184441d880>


## DF2¶

[2]:

from pymoo.problems.dynamic.df import DF2

plot = Scatter()

for t in np.linspace(0, 10.0, 100):
problem = DF2(time=t)

plot.show()

[2]:

<pymoo.visualization.scatter.Scatter at 0x7f1809f2cee0>


## DF3¶

[3]:

from pymoo.problems.dynamic.df import DF3

plot = Scatter()

for t in np.linspace(0, 10.0, 100):
problem = DF3(time=t)

plot.show()

[3]:

<pymoo.visualization.scatter.Scatter at 0x7f1809f2c490>


## DF4¶

[4]:

from pymoo.problems.dynamic.df import DF4

plot = Scatter()

for t in np.linspace(0, 10.0, 100):
problem = DF4(time=t)
plot.add(problem.pareto_front() + 2*t, plot_type="line", color="black", alpha=0.7)

plot.show()

[4]:

<pymoo.visualization.scatter.Scatter at 0x7f18083c9d00>


## DF5¶

[5]:

from pymoo.problems.dynamic.df import DF5

plot = Scatter()

for t in np.linspace(0, 2.0, 100):
problem = DF5(time=t)
plot.add(problem.pareto_front(n_pareto_points=300) + 2*t, plot_type="line", color="black", alpha=0.7)

plot.show()

[5]:

<pymoo.visualization.scatter.Scatter at 0x7f18082b3c70>


## DF6¶

[6]:

from pymoo.problems.dynamic.df import DF6

plot = Scatter()

for t in np.linspace(0, 2.0, 100):
problem = DF6(time=t)

plot.show()

[6]:

<pymoo.visualization.scatter.Scatter at 0x7f18080a40a0>


## DF7¶

[7]:

from pymoo.problems.dynamic.df import DF7

plot = Scatter()

for t in np.linspace(0, 1.0, 20):
problem = DF7(time=t)
plot.add(problem.pareto_front() + 2*t, plot_type="line", color="black", alpha=0.7)

plot.show()

[7]:

<pymoo.visualization.scatter.Scatter at 0x7f1808263dc0>


## DF8¶

[8]:

from pymoo.problems.dynamic.df import DF8

plot = Scatter()

for t in np.linspace(0, 2.0, 20):
problem = DF8(time=t)
plot.add(problem.pareto_front() + 4*t, plot_type="line", color="black", alpha=0.7)

plot.show()

[8]:

<pymoo.visualization.scatter.Scatter at 0x7f1803e904f0>


## DF9¶

[9]:

from pymoo.problems.dynamic.df import DF9

plot = Scatter()

for t in np.linspace(0, 2.0, 20):
problem = DF9(time=t)
plot.add(problem.pareto_front() + 2*t, plot_type="line", color="black", alpha=0.7)

plot.show()

[9]:

<pymoo.visualization.scatter.Scatter at 0x7f1803dc3130>


## DF10¶

[10]:

from pymoo.problems.dynamic.df import DF10
import matplotlib.pyplot as plt

for t in [0.0, 1.0, 1.5, 2.0]:

plot = Scatter()
problem = DF10(time=t)
plot.add(problem.pareto_front() + 2*t, plot_type="line", color="black", alpha=0.7)
plot.do()
plt.show()

print("DONE")

DONE


## DF11¶

[11]:

from pymoo.problems.dynamic.df import DF11
import matplotlib.pyplot as plt

for t in [0.0, 1.0, 1.5, 2.0]:

plot = Scatter()
problem = DF11(time=t)
plot.add(problem.pareto_front() + 2*t, plot_type="line", color="black", alpha=0.7)
plot.do()
plt.show()

print("DONE")

DONE


## DF12¶

[12]:

from pymoo.problems.dynamic.df import DF12
import matplotlib.pyplot as plt

for t in [0.0, 0.1, 0.2]:

plot = Scatter()
problem = DF12(time=t)
plot.do()
plt.show()

print("DONE")

DONE


## DF13¶

[13]:

from pymoo.problems.dynamic.df import DF13
import matplotlib.pyplot as plt

for t in [0.0, 0.2, 0.3, 0.4]:

plot = Scatter()
problem = DF13(time=t)
plot.do()
plt.show()

print("DONE")

DONE


## DF14¶

[14]:

from pymoo.problems.dynamic.df import DF14
import matplotlib.pyplot as plt

for t in [0.0, 0.2, 0.5, 1.0]:

plot = Scatter()
problem = DF13(time=t)

DONE