optiwindnet.MILP

Submodules

• optiwindnet.MILP.fscip
• optiwindnet.MILP.ortools
• optiwindnet.MILP.pyomo
• optiwindnet.MILP.scip

Package Contents

class optiwindnet.MILP.FeederLimit

Bases: enum.StrEnum

Whether to limit the maximum number of feeders, if set to “specified”,

Initialize self. See help(type(self)) for accurate signature.

UNLIMITED

SPECIFIED

MINIMUM

MIN_PLUS1

MIN_PLUS2

MIN_PLUS3

DEFAULT

class optiwindnet.MILP.FeederRoute

Bases: enum.StrEnum

If feeder routes must be “straight” or can be detoured (“segmented”).

Initialize self. See help(type(self)) for accurate signature.

STRAIGHT

SEGMENTED

DEFAULT

class optiwindnet.MILP.ModelMetadata

R: int

T: int

capacity: int

linkset: tuple[_Link, Ellipsis]

link_: collections.abc.Mapping[_Link, Any]

flow_: collections.abc.Mapping[_Link, Any]

model_options: dict[str, Any]

fun_fingerprint: dict[str, str | bytes]

weight_: tuple[float, Ellipsis] = ()

solution_hint: dict[Any, float]

warmed_by: str = ''

class optiwindnet.MILP.ModelOptions(**kwargs)

Bases: dict

Hold options for the modelling of the cable routing problem.

Use ModelOptions.help() to get the options and their permitted and default values. Use ModelOptions() without any parameters to use the defaults.

Initialize self. See help(type(self)) for accurate signature.

hints

simple

classmethod help()

exception optiwindnet.MILP.OWNSolutionNotFound

Bases: Exception

Common base class for all non-exit exceptions.

Initialize self. See help(type(self)) for accurate signature.

exception optiwindnet.MILP.OWNWarmupFailed

Bases: Exception

Common base class for all non-exit exceptions.

Initialize self. See help(type(self)) for accurate signature.

class optiwindnet.MILP.SolutionInfo

runtime: float

bound: float

objective: float

relgap: float

termination: str

class optiwindnet.MILP.Solver

Bases: abc.ABC

Common interface to multiple MILP solvers

name: str

metadata: ModelMetadata

solver: Any

options: dict[str, Any]

stopping: dict[str, Any]

solution_info: SolutionInfo

applied_options: dict[str, Any]

abstractmethod set_problem(P: networkx.PlanarEmbedding, A: networkx.Graph, capacity: int, model_options: ModelOptions, warmstart: networkx.Graph | None = None)

Define the problem geometry, available edges and tree properties

Parameters:

• P – planar embedding of the location

• A – available edges for the location

• capacity – maximum number of terminals in a subtree

• model_options – tree properties - see ModelOptions.help()

• warmstart – initial feasible solution to pass to solver

abstractmethod solve(time_limit: float, mip_gap: float, options: dict[str, Any] = {}, verbose: bool = False) → SolutionInfo

Run the MILP solver search.

Parameters:

• time_limit – maximum time (s) the solver is allowed to run.

• mip_gap – relative difference from incumbent solution to lower bound at which the search may be stopped before time_limit is reached.

• options – additional options to pass to solver (see solver manual).

Returns:

General information about the solution search (use get_solution() for

the actual solution).

abstractmethod get_solution(A: networkx.Graph | None = None) → tuple[networkx.Graph, networkx.Graph]

Output solution topology A and routeset G.

Parameters:

A – optionally replace the A given via set_problem() (if normalized A)

Returns:

Topology graph S and routeset G.

class optiwindnet.MILP.Topology

Bases: enum.StrEnum

Set the topology of subtrees in the solution.

Initialize self. See help(type(self)) for accurate signature.

RADIAL

BRANCHED

DEFAULT

optiwindnet.MILP.solver_factory(solver_name: str) → _core.Solver

Create a Solver object tied to the specified external MILP solver.

Note that the only solver that is a dependency of OptiWindNet is ‘ortools’. Check OptiWindNet’s documentation on how to install optional solvers.

Legacy compatibility: if solver_name == ‘ortools’ then the CP-SAT backend is used.

Parameters:

solver_name – one of ‘ortools.cp_sat’, ‘ortools.gscip’, ‘ortools.highs’, ‘cplex’, ‘gurobi’, ‘cbc’, ‘scip’, ‘highs’.

Returns:

Solver instance that can produce solutions for the cable routing problem.