Closed doup123 closed 3 years ago
Hi,
You can use the following code :
# define the problem definition
problem = DTLZ2()
# instantiate the optimization algorithm
algorithm = NSGAII(problem)
# optimize the problem using 10,000 function evaluations
algorithm.run(10000)
# display the results
for solution in algorithm.result:
print(solution.objectives)
# keep only solutions that are part of the Pareto Front
nondominated_solutions = nondominated(algorithm.result)
Please check the documentation for an intro to Platypus https://platypus.readthedocs.io/en/latest/
Is there a way to get and store all Pareto solutions?