def test_griewank_works_fine(self): ihc_griewank = HillClimbAlgorithm(D=self.D, nFES=self.nFES, nGEN=self.nGEN, benchmark=Griewank(), seed=self.seed) ihc_griewankc = HillClimbAlgorithm(D=self.D, nFES=self.nFES, nGEN=self.nGEN, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, ihc_griewank, ihc_griewankc)
def test_griewank_works_fine(self): hs_griewank = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=Griewank()) hs_griewankc = HarmonySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, seed=self.seed, benchmark=Griewank()) AlgorithmTestCase.algorithm_run_test(self, hs_griewank, hs_griewankc)
def test_griewank_works_fine(self): ca_griewank = CamelAlgorithm(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed) ca_griewankc = CamelAlgorithm(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, ca_griewank, ca_griewankc)
def test_griewank1_works_fine(self): es1_griewank = CovarianceMaatrixAdaptionEvolutionStrategy( D=self.D, nFES=self.nFES, nGEN=self.nGEN, benchmark=Griewank(), seed=self.seed) es1_griewankc = CovarianceMaatrixAdaptionEvolutionStrategy( D=self.D, nFES=self.nFES, nGEN=self.nGEN, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, es1_griewank, es1_griewankc)
def test_griewank1_works_fine(self): ca_griewank = SimulatedAnnealing(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed, coolingMethod=coolLinear) ca_griewankc = SimulatedAnnealing(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed, coolingMethod=coolLinear) AlgorithmTestCase.algorithm_run_test(self, ca_griewank, ca_griewankc)
def test_griewank_works_fine(self): fun = Griewank().function() x = self.gsa_griewank.run() self.assertTrue(x) self.assertAlmostEqual(fun(self.gsa_griewank.task.D, asarray(x[0])), x[1], delta=1e2)
def setUp(self): self.D = 40 self.hs_custom = HarmonySearchV1(D=self.D, nFES=1000, benchmark=MyBenchmark()) self.hs_griewank = HarmonySearchV1(D=self.D, nFES=1000, benchmark=Griewank())
def test_griewank_works_fine(self): mts_griewank = MultipleTrajectorySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, n=10, C_a=5, C_r=0.5, benchmark=Griewank(), seed=self.seed) mts_griewankc = MultipleTrajectorySearchV1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, n=10, C_a=5, C_r=0.5, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, mts_griewank, mts_griewankc)
def test_griewank_works_fine(self): es_griewank = EvolutionStrategy1p1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, k=15, c_a=1.2, c_r=0.5, benchmark=Griewank(), seed=self.seed) es_griewankc = EvolutionStrategy1p1(D=self.D, nFES=self.nFES, nGEN=self.nGEN, k=15, c_a=1.2, c_r=0.5, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, es_griewank, es_griewankc)
def test_griewank_works_fine(self): nmm_griewank = NelderMeadMethod(D=self.D, nFES=self.nFES, nGEN=self.nGEN, n=10, C_a=5, C_r=0.5, benchmark=Griewank(), seed=self.seed) nmm_griewankc = NelderMeadMethod(D=self.D, nFES=self.nFES, nGEN=self.nGEN, n=10, C_a=5, C_r=0.5, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, nmm_griewank, nmm_griewankc)
def setUp(self): self.D = 40 self.ihc_custom = HillClimbAlgorithm(D=self.D, nFES=1000, delta=0.4, benchmark=MyBenchmark()) self.ihc_griewank = HillClimbAlgorithm(D=self.D, nFES=1000, benchmark=Griewank())
def setUp(self): self.D = 40 self.bbfwa_custom = BareBonesFireworksAlgorithm( D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.bbfwa_griewank = BareBonesFireworksAlgorithm(D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def test_griewank_works_fine(self): sca_griewank = SineCosineAlgorithm(D=self.D, nFES=self.nFES, nGEN=self.nGEN, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank(), seed=self.seed) sca_griewankc = SineCosineAlgorithm(D=self.D, nFES=self.nFES, nGEN=self.nGEN, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, sca_griewank, sca_griewankc)
def test_griewank1_works_fine(self): es1_griewank = EvolutionStrategyML(D=self.D, nFES=self.nFES, nGEN=self.nGEN, mu=45, lam=35, k=25, c_a=1.5, c_r=0.5, benchmark=Griewank(), seed=self.seed) es1_griewankc = EvolutionStrategyML(D=self.D, nFES=self.nFES, nGEN=self.nGEN, mu=45, lam=35, k=25, c_a=1.5, c_r=0.5, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, es1_griewank, es1_griewankc)
def setUp(self): self.D = 40 self.mts_custom = MultipleTrajectorySearchV1(D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.mts_griewank = MultipleTrajectorySearchV1(D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def setUp(self): self.D = 40 self.aso_custom = AnarchicSocietyOptimization(NP=40, D=self.D, nGEN=10, nFES=4000, Combination=Crossover, benchmark=MyBenchmark()) self.aso_griewank = AnarchicSocietyOptimization(NP=40, D=self.D, nGEN=10, nFES=4000, Combination=Crossover, benchmark=Griewank())
def setUp(self): self.D = 40 self.nmm_custom = NelderMeadMethod(D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.nmm_griewank = NelderMeadMethod(D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def setUp(self): self.D = 40 self.efwa_custom = EnhancedFireworksAlgorithm(D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.efwa_griewank = EnhancedFireworksAlgorithm(D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def setUp(self): self.D = 40 self.kh_custom = KrillHerdV3(D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.kh_griewank = KrillHerdV3(D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def setUp(self): self.D = 40 self.sca_custom = SineCosineAlgorithm(D=self.D, nFES=1000, NP=35, a=7, Rmin=0.1, Rmax=3, benchmark=MyBenchmark()) self.sca_griewank = SineCosineAlgorithm(D=self.D, nFES=1000, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank())
def setUp(self): self.D = 40 self.gso_custom = GlowwormSwarmOptimizationV2(D=self.D, nFES=1000, NP=35, a=7, Rmin=0.1, Rmax=3, benchmark=MyBenchmark()) self.gso_griewank = GlowwormSwarmOptimizationV2(D=self.D, nFES=1000, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank())
def test_griewank_works_fine(self): fun = Griewank().function() x = self.bbfa_griewank.run() self.assertTrue(x) self.assertAlmostEqual(fun(self.D, x[0]), x[1], delta=1e2)
def test_griewank_works_fine(self): ca_griewank = DynNpMultiStrategyDifferentialEvolutionMTS(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed) ca_griewankc = DynNpMultiStrategyDifferentialEvolutionMTS(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, ca_griewank, ca_griewankc)
def setUp(self): self.D = 40 self.dfwa_custom = DynamicFireworksAlgorithmGauss( D=self.D, nFES=1000, n=10, C_a=2, C_r=0.5, benchmark=MyBenchmark()) self.dfwa_griewank = DynamicFireworksAlgorithmGauss( D=self.D, nFES=1000, n=10, C_a=5, C_r=0.5, benchmark=Griewank())
def test_griewank_works_fine(self): gso_griewank = GlowwormSwarmOptimizationV3(D=self.D, nFES=self.nFES, nGEN=self.nGEN, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank(), seed=self.seed) gso_griewankc = GlowwormSwarmOptimizationV3(D=self.D, nFES=self.nFES, nGEN=self.nGEN, NP=10, a=5, Rmin=0.01, Rmax=3, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, gso_griewank, gso_griewankc)
def setUp(self): self.D = 40 self.ca_custom = CamelAlgorithm(NP=40, D=self.D, nGEN=10, nFES=4000, benchmark=MyBenchmark()) self.ca_griewank = CamelAlgorithm(NP=40, D=self.D, nGEN=10, nFES=4000, benchmark=Griewank())
def test_griewank_works_fine(self): aso_griewank = AnarchicSocietyOptimization(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, Combination=Crossover, benchmark=Griewank(), seed=self.seed) aso_griewankc = AnarchicSocietyOptimization(NP=40, D=self.D, nGEN=self.nGEN, nFES=self.nFES, Combination=Crossover, benchmark=Griewank(), seed=self.seed) AlgorithmTestCase.algorithm_run_test(self, aso_griewank, aso_griewankc)
def setUp(self): self.D = 40 self.es_custom = EvolutionStrategy1p1(D=self.D, nFES=1000, k=10, c_a=1.5, c_r=0.42, benchmark=MyBenchmark()) self.es_griewank = EvolutionStrategy1p1(D=self.D, nFES=1000, k=15, c_a=1.2, c_r=0.5, benchmark=Griewank())
def setUp(self): self.D = 40 self.es_custom = EvolutionStrategyML(D=self.D, nFES=1000, mu=45, k=50, c_a=1.1, c_r=0.5, benchmark=MyBenchmark()) self.es1_custom = EvolutionStrategyML(D=self.D, nFES=1000, mu=45, lam=35, k=50, c_a=1.1, c_r=0.5, benchmark=MyBenchmark()) self.es_griewank = EvolutionStrategyML(D=self.D, nFES=1000, mu=35, lam=45, k=45, c_a=1.5, c_r=0.5, benchmark=Griewank()) self.es1_griewank = EvolutionStrategyML(D=self.D, nFES=1000, mu=45, lam=35, k=25, c_a=1.5, c_r=0.5, benchmark=Griewank())