def __init__(self,
              search_space,
              fitness_function,
              IDW,
              noisemap,
              x_y_limits,
              z_sigma,
              work_space,
              random_state,
              init_network,
              sample_point_distance,
              restricted_airspace,
              flight_constraints,
              geofence_point_boundary,
              minimization=True):
     Problem.__init__(self, search_space, fitness_function, minimization)
     self.IDW = IDW
     self.noisemap = noisemap
     self.x_y_limits = x_y_limits
     self.z_sigma = z_sigma
     self.work_space = work_space
     self.random_state = random_state
     self.init_network = init_network
     self.sample_point_distance = sample_point_distance
     self.endpoints = self._get_endpoints()
     self.restricted_airspace = restricted_airspace
     self.flight_constraints = flight_constraints
     self.geofence_point_boundary = geofence_point_boundary
    def __init__(self, **kwargs):
        Problem.__init__(self, **kwargs)

        self.jobs = {'quantity': 0, 'list': [], 'total_units': []}
        self.machines = {'quantity': 0, 'loadout_times': [], 'lower_bounds_taillard': [], 'assigned_jobs': []}

        # Load benchmark instance
        self.ilb = 0  # Instance lower bound
        self.iub = 0  # Instance upper bound
        self.load_instance()

        # Set n dimensions
        self.n = self.jobs['quantity']

        self.pre_processing_done = False
Example #3
0
 def __init__(
     self, decision_vector, objective_vector, solver, highs, lows, directions=None, is_empty=False, **settings
 ):
     Problem.__init__(self)
     if is_empty:
         return
     if not directions:
         directions = [True] * len(objective_vector)
     self.decisions = [Decision(dec.decl().name(), is_true(False), is_true(True)) for dec in decision_vector]
     self.objectives = [
         Objective(obj.decl().name(), directions[i], lows[i], highs[i]) for i, obj in enumerate(objective_vector)
     ]
     self.decision_vector = decision_vector
     self.objective_vector = objective_vector
     self.solver = solver
     self.base_solver = clone(solver)
     self.generation_counter = 0
    def __init__(self, **kwargs):
        Problem.__init__(self, **kwargs)

        # Set n dimensions
        self.n = 2