Source code for gemseo.algos.opt.augmented_lagrangian.order_1
# Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program; if not, write to the Free Software Foundation,
# Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
"""Augmented Lagrangian of order 1."""
from __future__ import annotations
from typing import TYPE_CHECKING
from gemseo.algos.design_space import DesignSpace
from gemseo.algos.lagrange_multipliers import LagrangeMultipliers
from gemseo.algos.opt.augmented_lagrangian.penalty_heuristic import (
AugmentedLagrangianPenaltyHeuristic,
)
from gemseo.algos.opt.optimization_library import OptimizationAlgorithmDescription
if TYPE_CHECKING:
from numpy import ndarray
[docs]
class AugmentedLagrangianOrder1(AugmentedLagrangianPenaltyHeuristic):
"""An augmented Lagrangian algorithm of order 1.
The Lagrange multipliers are updated using gradient information
computed using the :class:`.LagrangeMultipliers` class.
"""
__lagrange_multiplier_calculator: LagrangeMultipliers
"""The Lagrange multiplier calculator."""
def __init__(self) -> None: # noqa:D107
super().__init__()
self.__lagrange_multiplier_calculator = None
self.descriptions = {
"Augmented_Lagrangian_order_1": OptimizationAlgorithmDescription(
algorithm_name="Augmented_Lagrangian_order_1",
description=(
"Augmented Lagrangian algorithm using gradient information."
),
internal_algorithm_name="Augmented_Lagrangian",
handle_equality_constraints=True,
handle_inequality_constraints=True,
require_gradient=True,
),
}
def _update_lagrange_multipliers(
self, eq_lag: dict[str, ndarray], ineq_lag: dict[str, ndarray], x_opt: ndarray
) -> None: # noqa:D107
if self.__lagrange_multiplier_calculator is None:
self.__lagrange_multiplier_calculator = LagrangeMultipliers(self.problem)
lag_ms = self.__lagrange_multiplier_calculator.compute(x_opt)
for constraint in self.problem.constraints:
if constraint.name in ineq_lag and LagrangeMultipliers.INEQUALITY in lag_ms:
for var_compo_name, lag_value in zip(
lag_ms[LagrangeMultipliers.INEQUALITY][0],
lag_ms[LagrangeMultipliers.INEQUALITY][1],
):
if constraint.name in var_compo_name:
if DesignSpace.SEP in var_compo_name:
var_component_index = int(
var_compo_name.replace(constraint.name, "").replace(
DesignSpace.SEP, ""
)
)
ineq_lag[constraint.name][var_component_index] = lag_value
else:
ineq_lag[constraint.name] = lag_value
elif constraint.name in eq_lag and LagrangeMultipliers.EQUALITY in lag_ms:
for var_compo_name, lag_value in zip(
lag_ms[LagrangeMultipliers.EQUALITY][0],
lag_ms[LagrangeMultipliers.EQUALITY][1],
):
if constraint.name in var_compo_name:
if DesignSpace.SEP in var_compo_name:
var_component_index = int(
var_compo_name.replace(constraint.name, "").replace(
DesignSpace.SEP, ""
)
)
eq_lag[constraint.name][var_component_index] = lag_value
else:
eq_lag[constraint.name] = lag_value