Source code for jmetal.problem.multiobjective.constrained
from math import atan, cos, pi
from jmetal.core.problem import FloatProblem
from jmetal.core.solution import FloatSolution
"""
.. module:: constrained
:platform: Unix, Windows
:synopsis: Constrained test problems for multi-objective optimization
.. moduleauthor:: Antonio J. Nebro <antonio@lcc.uma.es>
"""
[docs]
class Srinivas(FloatProblem):
"""Class representing problem Srinivas."""
def __init__(self):
super(Srinivas, self).__init__()
number_of_variables = 2
self.obj_directions = [self.MINIMIZE, self.MINIMIZE]
self.obj_labels = ["f(x)", "f(y)"]
self.lower_bound = [-20.0 for _ in range(number_of_variables)]
self.upper_bound = [20.0 for _ in range(number_of_variables)]
[docs]
def number_of_objectives(self) -> int:
return len(self.obj_directions)
[docs]
def number_of_constraints(self) -> int:
return 2
[docs]
def evaluate(self, solution: FloatSolution) -> FloatSolution:
x1 = solution.variables[0]
x2 = solution.variables[1]
solution.objectives[0] = 2.0 + (x1 - 2.0) * (x1 - 2.0) + (x2 - 1.0) * (x2 - 1.0)
solution.objectives[1] = 9.0 * x1 - (x2 - 1.0) * (x2 - 1.0)
self.__evaluate_constraints(solution)
return solution
def __evaluate_constraints(self, solution: FloatSolution) -> None:
x1 = solution.variables[0]
x2 = solution.variables[1]
solution.constraints[0] = 1.0 - (x1 * x1 + x2 * x2) / 225.0
solution.constraints[1] = (3.0 * x2 - x1) / 10.0 - 1.0
[docs]
def name(self):
return "Srinivas"
[docs]
class Tanaka(FloatProblem):
"""Class representing problem Tanaka."""
def __init__(self):
super(Tanaka, self).__init__()
self.obj_directions = [self.MINIMIZE, self.MINIMIZE]
self.obj_labels = ["f(x)", "f(y)"]
number_of_variables = 2
self.lower_bound = [10e-5 for _ in range(number_of_variables)]
self.upper_bound = [pi for _ in range(number_of_variables)]
[docs]
def number_of_objectives(self) -> int:
return len(self.obj_directions)
[docs]
def number_of_constraints(self) -> int:
return 2
[docs]
def evaluate(self, solution: FloatSolution) -> FloatSolution:
solution.objectives[0] = solution.variables[0]
solution.objectives[1] = solution.variables[1]
self.__evaluate_constraints(solution)
return solution
def __evaluate_constraints(self, solution: FloatSolution) -> None:
constraints = [0.0 for _ in range(self.number_of_constraints())]
x1 = solution.variables[0]
x2 = solution.variables[1]
constraints[0] = x1 * x1 + x2 * x2 - 1.0 - 0.1 * cos(16.0 * atan(x1 / x2))
constraints[1] = -2.0 * ((x1 - 0.5) * (x1 - 0.5) + (x2 - 0.5) * (x2 - 0.5) - 0.5)
solution.constraints = constraints
# set_overall_constraint_violation_degree(solution)
[docs]
def name(self):
return "Tanaka"
[docs]
class Osyczka2(FloatProblem):
"""Class representing problem Osyczka2."""
def __init__(self):
super(Osyczka2, self).__init__()
self.obj_directions = [self.MINIMIZE, self.MINIMIZE]
self.obj_labels = ["f(x)", "f(y)"]
self.lower_bound = [0.0, 0.0, 1.0, 0.0, 1.0, 0.0]
self.upper_bound = [10.0, 10.0, 5.0, 6.0, 5.0, 10.0]
[docs]
def number_of_objectives(self) -> int:
return len(self.obj_directions)
[docs]
def number_of_constraints(self) -> int:
return 6
[docs]
def evaluate(self, solution: FloatSolution) -> FloatSolution:
x = solution.variables
solution.objectives[0] = -(
25.0 * (x[0] - 2.0) ** 2 + (x[1] - 2.0) ** 2 + (x[2] - 1.0) ** 2 + (x[3] - 4.0) ** 2 + (x[4] - 1.0) ** 2
)
solution.objectives[1] = sum([x[i] ** 2 for i in range(len(x))])
self.__evaluate_constraints(solution)
return solution
def __evaluate_constraints(self, solution: FloatSolution) -> None:
constraints = [0.0 for _ in range(self.number_of_constraints())]
x = solution.variables
constraints[0] = (x[0] + x[1]) / 2.0 - 1.0
constraints[1] = (6.0 - x[0] - x[1]) / 6.0
constraints[2] = (2.0 - x[1] + x[0]) / 2.0
constraints[3] = (2.0 - x[0] + 3.0 * x[1]) / 2.0
constraints[4] = (4.0 - (x[2] - 3.0) * (x[2] - 3.0) - x[3]) / 4.0
constraints[5] = ((x[4] - 3.0) * (x[4] - 3.0) + x[5] - 4.0) / 4.0
solution.constraints = constraints
[docs]
def name(self):
return "Osyczka2"
[docs]
class Binh2(FloatProblem):
"""Class representing problem Binh2."""
def __init__(self):
super(Binh2, self).__init__()
self.obj_directions = [self.MINIMIZE, self.MINIMIZE]
self.obj_labels = ["f(x)", "f(y)"]
self.lower_bound = [0.0, 0.0]
self.upper_bound = [5.0, 3.0]
[docs]
def number_of_objectives(self) -> int:
return len(self.obj_directions)
[docs]
def number_of_constraints(self) -> int:
return 2
[docs]
def evaluate(self, solution: FloatSolution) -> FloatSolution:
x = solution.variables
solution.objectives[0] = 4.0 * x[0] * x[0] + 4 * x[1] * x[1]
solution.objectives[1] = (x[0] - 5.0) * (x[0] - 5.0) + (x[1] - 5.0) * (x[1] - 5.0)
self.__evaluate_constraints(solution)
return solution
def __evaluate_constraints(self, solution: FloatSolution) -> None:
constraints = [0.0 for _ in range(self.number_of_constraints())]
x = solution.variables
constraints[0] = -1.0 * (x[0] - 5) * (x[0] - 5) - x[1] * x[1] + 25.0
constraints[1] = (x[0] - 8) * (x[0] - 8) + (x[1] + 3) * (x[1] + 3) - 7.7
[docs]
def name(self):
return "Binh2"
