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)