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())