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)