def test_case_3(self):
# prepare raw problem
variables = [0, 1, 2, 3]
objectives = [{0: -10, 1: -5, 2: -1, 3: -5}, {0: 3, 1: 2, 2: 3, 3: 0}]
constraints = dict()
# prepare solvers
for solver_name in self.binary_solver:
if solver_name == 'epsilon':
problem = NextReleaseProblem.MOIP( \
variables, objectives, constraints, \
dict(), dict() \
)
else:
constraints = JNRP.regularize_constraints(
constraints, len(variables))
problem = JNRP(variables, objectives, constraints)
solver = Solver(solver_name)
# prepare and solve
solver.load(problem)
solver.execute()
# get the solutions
solutions = solver.solutions()
print(solver_name + '\t\t' + str(len(solutions)))
self.display(solutions, 5)
def test_case_2(self):
# prepare raw problem
variables = [0, 1, 2, 3]
objectives = [{0: -10, 1: -5, 2: -1, 3: 5}]
constraints = [{2: 1, 4: 0}, {0: 1, 3: -1, 4: 0}]
# prepare solvers
for solver_name in self.single_solver:
if solver_name == 'single':
problem = NextReleaseProblem.MOIP( \
variables, objectives, constraints, \
['L' for _ in range(len(constraints))], dict() \
)
else:
constraints = JNRP.regularize_constraints(
constraints, len(variables))
problem = JNRP(variables, objectives, constraints)
solver = Solver(solver_name)
# prepare and solve
solver.load(problem)
solver.execute()
# get the solutions
solutions = solver.solutions()
print(solver_name + '\t\t' + str(len(solutions)))
self.display(solutions, 5)
