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())