def test_custom_works_fine(self):
jde_custom = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
D=self.D,
NP=40,
nFES=self.nFES,
nGEN=self.nGEN,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
benchmark=MyBenchmark(),
seed=self.seed)
jde_customc = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
D=self.D,
NP=40,
nFES=self.nFES,
nGEN=self.nGEN,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
benchmark=MyBenchmark(),
seed=self.seed)
AlgorithmTestCase.algorithm_run_test(self, jde_custom, jde_customc)
def test_griewank_works_fine(self):
jde_griewank = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
D=self.D,
NP=40,
nFES=self.nFES,
nGEN=self.nGEN,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
benchmark='griewank',
seed=self.seed)
jde_griewankc = MultiStrategySelfAdaptiveDifferentialEvolution(
D=self.D,
NP=40,
nFES=self.nFES,
nGEN=self.nGEN,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
benchmark='griewank',
seed=self.seed)
AlgorithmTestCase.algorithm_run_test(self, jde_griewank, jde_griewankc)
def test_custom_works_fine(self):
jde_custom = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
NP=40,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
seed=self.seed)
jde_customc = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
NP=40,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, jde_custom, jde_customc,
MyBenchmark())
def test_griewank_works_fine(self):
jde_griewank = DynNpMultiStrategySelfAdaptiveDifferentialEvolution(
NP=40,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
seed=self.seed)
jde_griewankc = MultiStrategySelfAdaptiveDifferentialEvolution(
NP=40,
F=0.5,
F_l=0.0,
F_u=2.0,
Tao1=0.9,
CR=0.1,
Tao2=0.45,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, jde_griewank, jde_griewankc)