def setUp(self):
self.D, self.F, self.CR = 10, 0.9, 0.3
self.x, self.task = default_rng().uniform(
10, 50, self.D), Task(problem=MyProblem(self.D))
self.s1, self.s2 = SolutionJDE(task=self.task, e=False), SolutionJDE(
differential_weight=self.F,
crossover_probability=self.CR,
x=self.x)
def test_custom(self):
cro_custom = self.algo(population_size=10, seed=self.seed)
cro_customc = self.algo(population_size=10, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self,
cro_custom,
cro_customc,
MyProblem(),
max_iters=100)
def test_custom(self):
jde_custom = SelfAdaptiveDifferentialEvolution(f_lower=0.0, f_upper=2.0, tao1=0.9, tao2=0.45,
population_size=10, differential_weight=0.5,
crossover_probability=0.1, seed=self.seed)
jde_customc = SelfAdaptiveDifferentialEvolution(f_lower=0.0, f_upper=2.0, tao1=0.9, tao2=0.45,
population_size=10, differential_weight=0.5,
crossover_probability=0.1, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, jde_custom, jde_customc, MyProblem())
def test_custom1(self):
ca_custom = self.algo(population_size=10,
seed=self.seed,
cooling_method=cool_linear)
ca_customc = self.algo(population_size=10,
seed=self.seed,
cooling_method=cool_linear)
AlgorithmTestCase.test_algorithm_run(self, ca_custom, ca_customc,
MyProblem())
def test_custom(self):
aso_custom = self.algo(population_size=10,
combination=crossover,
seed=self.seed)
aso_customc = self.algo(population_size=10,
combination=crossover,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, aso_custom, aso_customc,
MyProblem())
def test_custom(self):
fwa_custom = self.algo(population_size=10, seed=self.seed)
fwa_customc = self.algo(population_size=10, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self,
fwa_custom,
fwa_customc,
MyProblem(),
max_evals=12345,
max_iters=17)
def test_Custom(self):
de_custom = self.algo(population_size=10,
differential_weight=0.5,
crossover_probability=0.9,
seed=self.seed)
de_customc = self.algo(population_size=10,
differential_weight=0.5,
crossover_probability=0.9,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, de_custom, de_customc,
MyProblem())
def test_custom(self):
kh_custom = self.algo(population_size=10,
C_a=2,
C_r=0.5,
seed=self.seed)
kh_customc = self.algo(population_size=10,
C_a=2,
C_r=0.5,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, kh_custom, kh_customc,
MyProblem())
def test_custom(self):
bbfwa_custom = self.algo(num_sparks=10,
amplification_coefficient=2,
reduction_coefficient=0.5,
seed=self.seed)
bbfwa_customc = self.algo(num_sparks=10,
amplification_coefficient=2,
reduction_coefficient=0.5,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, bbfwa_custom, bbfwa_customc,
MyProblem())
def test(self):
fa = self.algo(population_size=10,
alpha=0.5,
beta_min=0.2,
gamma=1.0,
seed=self.seed)
fac = self.algo(population_size=10,
alpha=0.5,
beta_min=0.2,
gamma=1.0,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, fa, fac, MyProblem())
def test_custom(self):
sca_custom = self.algo(population_size=35,
a=7,
r_min=0.1,
r_max=3,
seed=self.seed)
sca_customc = self.algo(population_size=35,
a=7,
r_min=0.1,
r_max=3,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, sca_custom, sca_customc,
MyProblem())
def test_custom(self):
ca_custom = self.algo(population_size=10,
num_tests=1,
num_searches=2,
num_enabled=2,
seed=self.seed)
ca_customc = self.algo(population_size=10,
num_tests=1,
num_searches=2,
num_enabled=2,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, ca_custom, ca_customc,
MyProblem())
def test_custom(self):
gso_custom = self.algo(population_size=10,
a=7,
Rmin=0.1,
Rmax=3,
seed=self.seed)
gso_customc = self.algo(population_size=10,
a=7,
Rmin=0.1,
Rmax=3,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, gso_custom, gso_customc,
MyProblem())
def test_custom(self):
ga_custom = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=0.4,
seed=self.seed)
ga_customc = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=0.4,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, ga_custom, ga_customc,
MyProblem())
def test_custom(self):
mts_custom = self.algo(population_size=10,
C_a=2,
C_r=0.5,
seed=self.seed)
mts_customc = self.algo(population_size=10,
C_a=2,
C_r=0.5,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self,
mts_custom,
mts_customc,
MyProblem(),
max_iters=100)
def test_custom(self):
ba_custom = self.algo(population_size=10,
loudness=0.5,
pulse_rate=0.5,
min_frequency=0.0,
max_frequency=2.0,
seed=self.seed)
ba_customc = self.algo(population_size=10,
loudness=0.5,
pulse_rate=0.5,
min_frequency=0.0,
max_frequency=2.0,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, ba_custom, ba_customc,
MyProblem())
def test_custom(self):
bfoa_custom = self.algo(population_size=10,
n_chemotactic=100,
n_reproduction=4,
n_elimination=1,
step_size=0.1,
seed=self.seed)
bfoa_customc = self.algo(population_size=10,
n_chemotactic=100,
n_reproduction=4,
n_elimination=1,
step_size=0.1,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, bfoa_custom, bfoa_customc,
MyProblem())
def test_mutation_uros_c(self):
ga_crmt = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=0.4,
mutation=mutation_uros,
seed=self.seed)
ga_crmtc = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=0.4,
mutation=mutation_uros,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, ga_crmt, ga_crmtc,
MyProblem())
def test_custom1(self):
es1_custom = self.algo(mu=10,
lam=45,
k=50,
c_a=1.1,
c_r=0.5,
seed=self.seed)
es1_customc = self.algo(mu=10,
lam=45,
k=50,
c_a=1.1,
c_r=0.5,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, es1_custom, es1_customc,
MyProblem())
def test_multi_point_crossover_fine_c(self):
ga_mpcr = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=4,
crossover=multi_point_crossover,
seed=self.seed)
ga_mpcrc = self.algo(population_size=10,
tournament_size=4,
mutation_rate=0.05,
crossover_rate=4,
crossover=multi_point_crossover,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, ga_mpcr, ga_mpcrc,
MyProblem())
def test_custom(self):
bea = self.algo(population_size=10,
m=5,
e=4,
nep=5,
nsp=5,
ngh=2,
seed=self.seed)
beac = self.algo(population_size=10,
m=5,
e=4,
nep=5,
nsp=5,
ngh=2,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, bea, beac, MyProblem())
def test(self):
foa = self.algo(population_size=10,
lifetime=5,
local_seeding_changes=1,
global_seeding_changes=1,
area_limit=20,
transfer_rate=0.35,
seed=self.seed)
foac = self.algo(population_size=10,
lifetime=5,
local_seeding_changes=1,
global_seeding_changes=1,
area_limit=20,
transfer_rate=0.35,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, foa, foac, MyProblem())
def test_custom(self):
wvcpso_custom = ParticleSwarmAlgorithm(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
wvcpso_customc = ParticleSwarmAlgorithm(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, wvcpso_custom,
wvcpso_customc, MyProblem())
def test_custom(self):
clpso_custom = self.algo(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
clpso_customc = self.algo(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, clpso_custom, clpso_customc,
MyProblem())
def test_custom(self):
mpso_custom = MutatedParticleSwarmOptimization(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
mpso_customc = MutatedParticleSwarmOptimization(population_size=10,
c1=2.0,
c2=2.0,
w=0.7,
min_velocity=-4,
max_velocity=4,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, mpso_custom, mpso_customc,
MyProblem())
def test_custom(self):
hba_custom = self.algo(population_size=10,
loudness=0.5,
pulse_rate=0.5,
differential_weight=0.5,
crossover_probability=0.9,
min_frequency=0.0,
max_frequency=2.0,
seed=self.seed)
hba_customc = self.algo(population_size=10,
loudness=0.5,
pulse_rate=0.5,
differential_weight=0.5,
crossover_probability=0.9,
min_frequency=0.0,
max_frequency=2.0,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, hba_custom, hba_customc,
MyProblem())
def test_custom(self):
aba_custom = AdaptiveBatAlgorithm(population_size=10,
A=.75,
epsilon=2,
alpha=0.65,
r=0.7,
Qmin=0.0,
Qmax=2.0,
seed=self.seed)
aba_customc = AdaptiveBatAlgorithm(population_size=10,
A=.75,
epsilon=2,
alpha=0.65,
r=0.7,
Qmin=0.0,
Qmax=2.0,
seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, aba_custom, aba_customc,
MyProblem())
def test_custom(self):
"""Test case for running algorithm on custom problem."""
hsaba_custom = self.algo(population_size=10, Limit=2, seed=self.seed)
hsaba_customc = self.algo(population_size=10, Limit=2, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, hsaba_custom, hsaba_customc,
MyProblem())
def test_custom(self):
fpa_custom = self.algo(population_size=10, p=0.5, seed=self.seed)
fpa_customc = self.algo(population_size=10, p=0.5, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, fpa_custom, fpa_customc, MyProblem())
def test_custom(self):
hho_custom = self.algo(population_size=10, levy=0.01, seed=self.seed)
hho_customc = self.algo(population_size=10, levy=0.01, seed=self.seed)
AlgorithmTestCase.test_algorithm_run(self, hho_custom, hho_customc,
MyProblem())
