示例#1
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 def test_custom_works_fine(self):
     ca_custom = MultiStrategyDifferentialEvolutionMTSv1(NP=40,
                                                         seed=self.seed)
     ca_customc = MultiStrategyDifferentialEvolutionMTSv1(NP=40,
                                                          seed=self.seed)
     AlgorithmTestCase.algorithm_run_test(self, ca_custom, ca_customc,
                                          MyBenchmark())
示例#2
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# encoding=utf8
# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys

sys.path.append('../')
# End of fix

from NiaPy.algorithms.modified import MultiStrategyDifferentialEvolutionMTSv1
from NiaPy.algorithms.basic.de import CrossCurr2Best1, CrossBest1
from NiaPy.task.task import StoppingTask, OptimizationType
from NiaPy.benchmarks import Sphere

# we will run Differential Evolution for 5 independent runs
for i in range(5):
    task = StoppingTask(D=10,
                        nFES=5000,
                        optType=OptimizationType.MINIMIZATION,
                        benchmark=Sphere())
    algo = MultiStrategyDifferentialEvolutionMTSv1(
        NP=70, F=0.5, CR=0.4, strategies=(CrossBest1, CrossCurr2Best1))
    best = algo.run(task=task)
    print('%s -> %s' % (best[0].x, best[1]))

# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3
示例#3
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 def test_griewank_works_fine(self):
     ca_griewank = MultiStrategyDifferentialEvolutionMTSv1(NP=40,
                                                           seed=self.seed)
     ca_griewankc = MultiStrategyDifferentialEvolutionMTSv1(NP=40,
                                                            seed=self.seed)
     AlgorithmTestCase.algorithm_run_test(self, ca_griewank, ca_griewankc)
示例#4
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# encoding=utf8
# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys
sys.path.append('../')
# End of fix

from NiaPy.algorithms.modified import MultiStrategyDifferentialEvolutionMTSv1
from NiaPy.algorithms.basic.de import CrossRand1, CrossBest1
from NiaPy.task import StoppingTask
from NiaPy.benchmarks import Sphere

# we will run Differential Evolution for 5 independent runs
for i in range(5):
    task = StoppingTask(D=10, nFES=10000, benchmark=Sphere())
    algo = MultiStrategyDifferentialEvolutionMTSv1(NP=50,
                                                   F=0.5,
                                                   CR=0.9,
                                                   strategies=(CrossBest1,
                                                               CrossRand1))
    best = algo.run(task)
    print('%s -> %s' % (best[0], best[1]))

# vim: tabstop=3 noexpandtab shiftwidth=3 softtabstop=3