from desdeo_problem.problem.Variable import Variable
from desdeo_problem.problem.Objective import ScalarObjective
from desdeo_problem.problem.Problem import MOProblem
import numpy as np
[docs]def dummy_problem() -> MOProblem:
"""An example on how to implement a problem with 3 objectives and 4 variables and no constraints.
Returns:
MOProblem: a problem object.
"""
def f1(x: np.ndarray) -> np.ndarray:
x = np.atleast_2d(x)
# sum the rows
return np.sum(x, axis=1)
def f2(x: np.ndarray) -> np.ndarray:
x = np.atleast_2d(x)
return -np.sum(x, axis=1)
def f3(x: np.ndarray) -> np.ndarray:
x = np.atleast_2d(x)
# take the product of the rows
return np.prod(x, axis=1)
# args: name of objective, evaluator
objective_1 = ScalarObjective("F1", f1)
objective_2 = ScalarObjective("F2", f2)
objective_3 = ScalarObjective("F3", f3)
objectives = [objective_1, objective_2, objective_3]
# args: name of variable, initial value, lower bound, upper bound
variable_1 = Variable("x1", 3, 0, 5)
variable_2 = Variable("x2", 3, 2, 4)
variable_3 = Variable("x3", -2, -3, 4)
variable_4 = Variable("x4", -1, -6, 4)
variables = [variable_1, variable_2, variable_3, variable_4]
# instantiate MOProblem object
problem = MOProblem(objectives, variables)
return problem
