| # Copyright 2022 NNAISENSE SA | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import torch | |
| from evotorch import Problem | |
| from evotorch.algorithms import GeneticAlgorithm | |
| from evotorch.logging import StdOutLogger | |
| from evotorch.operators import GaussianMutation, SimulatedBinaryCrossOver | |
| # Kursawe function with two conflicting objectives | |
| # Non-vectorized (evaluates a single solution vector) for illustrative purposes | |
| def kursawe(x: torch.Tensor) -> torch.Tensor: | |
| f1 = torch.sum(-10 * torch.exp(-0.2 * torch.sqrt(x[0:2] ** 2.0 + x[1:3] ** 2.0)), dim=-1) | |
| f2 = torch.sum((torch.abs(x) ** 0.8) + (5 * torch.sin(x**3)), dim=-1) | |
| fitnesses = torch.stack([f1, f2], dim=-1) | |
| return fitnesses | |
| problem = Problem( | |
| # Two objectives, both minimization | |
| ["min", "min"], | |
| kursawe, | |
| initial_bounds=(-5.0, 5.0), | |
| solution_length=3, | |
| vectorized=False, | |
| # Create as many parallel Ray actors as there are available CPUs | |
| num_actors="max", | |
| ) | |
| # Run a GA similar to NSGA-II for 100 steps and log results to standard output every 10 steps | |
| searcher = GeneticAlgorithm( | |
| problem, | |
| popsize=200, | |
| operators=[ | |
| SimulatedBinaryCrossOver(problem, tournament_size=4, cross_over_rate=1.0, eta=8), | |
| GaussianMutation(problem, stdev=0.03), | |
| ], | |
| ) | |
| logger = StdOutLogger(searcher, interval=10) | |
| searcher.run(100) | |
| print("Final status:\n", searcher.status) | |