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Model Module

This section documents the model components of the Nextmv Gurobi Python SDK.

model

Defines gurobipy model interoperability.

This module provides functions for integrating Nextmv with Gurobi optimization.

FUNCTION DESCRIPTION
Model

Creates a Gurobi model that can be used to solve optimization problems.

Model 

Model(
    options: Options, license_path: Optional[str] = ""
) -> Model

Creates a Gurobi model, using Nextmv options.

You can import the Model function directly from nextmv_gurobipy:

from nextmv_gurobipy import Model

The returned type is a gurobipy.Model class. This means that once the Gurobi model is created, it can be used as any other Gurobi model. This loader will look for the gurobi.lic file in the provided license_path. If the file is not found, it will not be read. This means that by default, you will be working with Gurobi's community license.

Only the parameters that are available in the Gurobi API are set. If a parameter is not available, it will be skipped.

This function has some side effects that you should be aware of: - It redirects the solver chatter to stderr. - It sets the provider to "gurobi" in the options.

PARAMETER DESCRIPTION

options

The options for the Gurobi model. Any option that matches a Gurobi parameter name will be set in the model.

TYPE: Options

license_path

Path to the directory containing the Gurobi license file. Default is "" (empty string).

TYPE: str DEFAULT: ''

RETURNS DESCRIPTION
Model

The Gurobi model instance that can be used to define and solve optimization problems.

Examples:

>>> import nextmv
>>> from nextmv_gurobipy import Model
>>>
>>> # Create options
>>> options = nextmv.Options()
>>> options.threads = 4
>>> options.time_limit = 60
>>>
>>> # Create Gurobi model with Nextmv options
>>> model = Model(options, license_path="/path/to/license/directory")
>>>
>>> # Use model as any other Gurobi model
>>> x = model.addVar(name="x")
>>> y = model.addVar(name="y")
>>> model.addConstr(x + y <= 1)
>>> model.setObjective(x + y, sense=gp.GRB.MAXIMIZE)
>>> model.optimize()
Source code in nextmv-gurobipy/nextmv_gurobipy/model.py 
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def Model(options: nextmv.Options, license_path: Optional[str] = "") -> gp.Model:
    """
    Creates a Gurobi model, using Nextmv options.

    You can import the `Model` function directly from `nextmv_gurobipy`:

    ```python
    from nextmv_gurobipy import Model
    ```

    The returned type is a `gurobipy.Model` class. This means that once the Gurobi
    model is created, it can be used as any other Gurobi model. This loader will
    look for the `gurobi.lic` file in the provided `license_path`. If the file
    is not found, it will not be read. This means that by default, you will be
    working with Gurobi's community license.

    Only the parameters that are available in the Gurobi API are set. If a
    parameter is not available, it will be skipped.

    This function has some side effects that you should be aware of:
    - It redirects the solver chatter to stderr.
    - It sets the provider to "gurobi" in the options.

    Parameters
    ----------
    options : nextmv.Options
        The options for the Gurobi model. Any option that matches a Gurobi
        parameter name will be set in the model.
    license_path : str, optional
        Path to the directory containing the Gurobi license file.
        Default is "" (empty string).

    Returns
    -------
    gp.Model
        The Gurobi model instance that can be used to define and solve
        optimization problems.

    Examples
    --------
    >>> import nextmv
    >>> from nextmv_gurobipy import Model
    >>>
    >>> # Create options
    >>> options = nextmv.Options()
    >>> options.threads = 4
    >>> options.time_limit = 60
    >>>
    >>> # Create Gurobi model with Nextmv options
    >>> model = Model(options, license_path="/path/to/license/directory")
    >>>
    >>> # Use model as any other Gurobi model
    >>> x = model.addVar(name="x")
    >>> y = model.addVar(name="y")
    >>> model.addConstr(x + y <= 1)
    >>> model.setObjective(x + y, sense=gp.GRB.MAXIMIZE)
    >>> model.optimize()
    """

    # Solver chatter is logged to stderr.
    nextmv.redirect_stdout()

    env = gp.Env(empty=True)

    file_path = os.path.join(license_path, "gurobi.lic")
    if os.path.isfile(file_path):
        env.readParams(file_path)

    env.start()
    model = gp.Model(env=env)

    gp_names = [val["name"] for val in param_details.values()]
    for opt in options.options:
        name = opt.name
        if name not in gp_names:
            continue

        model.setParam(name, getattr(options, name))

    options.provider = "gurobi"

    return model