gemseo / algos / opt

lib_scipy_milp module¶

SciPy linear programming library wrapper.

class gemseo.algos.opt.lib_scipy_milp.ScipyMILP[source]

Bases: OptimizationLibrary

SciPy Mixed Integer Linear Programming library interface.

See OptimizationLibrary.

With respect to scipy milp function, this wrapper only allows continuous or integer variables.

Notes

The missing current values of the DesignSpace attached to the OptimizationProblem are automatically initialized with the method DesignSpace.initialize_missing_current_values().

Constructor.

Generate the library dictionary that contains the list of algorithms with their characteristics.

LIBRARY_NAME: ClassVar[str | None] = 'SciPy': The name of the interfaced library.

LIB_COMPUTE_GRAD = True

OPTIONS_MAP: ClassVar[dict[int, str]] = {'max_iter': 'node_limit'}: The names of the options in GEMSEO mapping to those in the wrapped library.

algo_name: str | None: The name of the algorithm used currently.

descriptions: dict[str, AlgorithmDescription]: The description of the algorithms contained in the library.

internal_algo_name: str | None

The internal name of the algorithm used currently.

It typically corresponds to the name of the algorithm in the wrapped library if any.

opt_grammar: JSONGrammar | None: The grammar defining the options of the current algorithm.

problem: OptimizationProblem: The optimization problem the driver library is bonded to.

class gemseo.algos.opt.lib_scipy_milp.ScipyMILPAlgorithmDescription(algorithm_name, internal_algorithm_name, library_name='SciPy', description='', website='', handle_integer_variables=True, require_gradient=False, handle_equality_constraints=True, handle_inequality_constraints=True, handle_multiobjective=False, positive_constraints=False, problem_type=ProblemType.LINEAR)[source]

Bases: OptimizationAlgorithmDescription

The description of a MILP optimization algorithm from the SciPy library.

Parameters:

algorithm_name (str) –
internal_algorithm_name (str) –
library_name (str) –

By default it is set to “SciPy”.
description (str) –

By default it is set to “”.
website (str) –

By default it is set to “”.
handle_integer_variables (bool) –

By default it is set to True.
require_gradient (bool) –

By default it is set to False.
handle_equality_constraints (bool) –

By default it is set to True.
handle_inequality_constraints (bool) –

By default it is set to True.
handle_multiobjective (bool) –

By default it is set to False.
positive_constraints (bool) –

By default it is set to False.
problem_type (ProblemType) –

By default it is set to “linear”.

algorithm_name: str: The name of the algorithm in GEMSEO.

handle_equality_constraints: bool = True: Whether the optimization algorithm handles equality constraints.

handle_inequality_constraints: bool = True: Whether the optimization algorithm handles inequality constraints.

handle_integer_variables: bool = True: Whether the optimization algorithm handles integer variables.

internal_algorithm_name: str: The name of the algorithm in the wrapped library.

library_name: str = 'SciPy': The name of the wrapped library.

problem_type: ProblemType = 'linear': The type of problem (see OptimizationProblem.ProblemType).