def test_hypervolume3D(self):
"""test the hypervolume in 3D"""
population = []
for i in range(10):
population.append(self.rmnk3D.generate_random_solution())
self.assertEqual(compute_hypervolume(population, [0, 0, 0]),
0.16108679722159508) # test the hypervolume value
def test_numerical_moead(self):
"""Test MOEA/D algorithm with ZDT1"""
moead = Moead(problem=self.zdt1,
max_evaluation=self.number_of_evaluations,
number_of_objective=self.number_of_objective,
number_of_weight=self.number_of_weight,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
weight_file=self.weight_file,
aggregation_function=Tchebycheff
)
non_dominated = moead.run()
self.assertEqual(len(non_dominated), 6) # test the number of non_dominated solutions
self.assertEqual(compute_hypervolume(non_dominated, [11, 11]), 91.30063166767695) # test the hypervolume value
def test_moead(self):
"""Test MOEA/D algorithm"""
moead = Moead(problem=self.rmnk,
max_evaluation=self.number_of_evaluations,
number_of_weight=self.number_of_weight,
aggregation_function=Tchebycheff,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
number_of_crossover_points=self.number_of_crossover_points,
weight_file=self.weight_file,
)
non_dominated = moead.run()
self.assertEqual(len(non_dominated), 8) # test the number of non_dominated solutions
self.assertEqual(compute_hypervolume(non_dominated, [0, 0]), 0.3079835420196539) # test the hypervolume value
def test_moead_sps_random(self):
"""Test MOEA/D algorithm with the random sps strategy"""
number_of_subproblem = 2
moead = MoeadSPSRandom(problem=self.rmnk,
max_evaluation=self.number_of_evaluations,
number_of_objective=self.number_of_objective,
aggregation_function=Tchebycheff,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
number_of_crossover_points=self.number_of_crossover_points,
number_of_subproblem_to_visit=number_of_subproblem,
weight_file=self.weight_file,
)
non_dominated = moead.run()
self.assertEqual(len(non_dominated), 10) # test the number of non_dominated solutions
self.assertEqual(compute_hypervolume(non_dominated, [0, 0]), 0.30882255276025106) # test the hypervolume value
def test_moead_dra(self):
"""Test MOEA/D algorithm with the random sps strategy"""
delta = 0.9
nr = 2
moead = MoeadDRA(problem=self.rmnk,
max_evaluation=500,
number_of_objective=self.number_of_objective,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
aggregation_function=Tchebycheff,
number_of_crossover_points=self.number_of_crossover_points,
weight_file=self.weight_file50,
delta=delta,
number_of_replacement=nr
)
non_dominated = moead.run()
self.assertEqual(len(non_dominated), 9) # test the number of non_dominated solutions
self.assertEqual(compute_hypervolume(non_dominated, [0, 0]), 0.3429102682198655) # test the hypervolume value
def test_moead_delta_nr(self):
"""Test MOEA/D algorithm with parameters delta & nr"""
delta = 0.9
nr = 2
moead = MoeadDeltaNr(problem=self.rmnk,
max_evaluation=self.number_of_evaluations,
number_of_objective=self.number_of_objective,
number_of_weight_neighborhood=self.number_of_weight_neighborhood,
number_of_crossover_points=self.number_of_crossover_points,
aggregation_function=Tchebycheff,
weight_file=self.weight_file,
delta=delta,
number_of_replacement=nr
)
non_dominated = moead.run()
self.assertEqual(len(non_dominated), 12) # test the number of non_dominated solutions
self.assertEqual(compute_hypervolume(non_dominated, [0, 0]), 0.3087417993003917) # test the hypervolume value