lumix.linearization.engine.LXLinearizer

class lumix.linearization.engine.LXLinearizer(model, solver_capability, config=None)

Automatic linearization engine.

Transforms nonlinear expressions into linear equivalents by: - Detecting nonlinear terms in model - Checking solver capabilities - Applying appropriate linearization techniques - Adding auxiliary variables and constraints

Example

linearizer = LXLinearizer(model, solver_capability, config)

if linearizer.needs_linearization():

linearized_model = linearizer.linearize_model()

Parameters:

• model (LXModel)

• solver_capability (LXSolverCapability)

• config (LXLinearizerConfig | None)

__init__(model, solver_capability, config=None)

Initialize linearization engine.

Parameters:

• model (LXModel) – Model to linearize

• solver_capability (LXSolverCapability) – Solver capability information

• config (Optional[LXLinearizerConfig]) – Linearization configuration (default: LXLinearizerConfig())

Methods

__init__(model, solver_capability[, config])	Initialize linearization engine.
get_statistics()	Get linearization statistics.
linearize_model()	Linearize the entire model.
needs_linearization()	Check if model contains nonlinear terms requiring linearization.

__init__(model, solver_capability, config=None)

Initialize linearization engine.

Parameters:

• model (LXModel) – Model to linearize

• solver_capability (LXSolverCapability) – Solver capability information

• config (Optional[LXLinearizerConfig]) – Linearization configuration (default: LXLinearizerConfig())

needs_linearization()

Check if model contains nonlinear terms requiring linearization.

Return type:

bool

Returns:

True if linearization is needed

linearize_model()

Linearize the entire model.

Creates a new model with: - All original variables and constraints - Auxiliary variables for linearized terms - Auxiliary constraints for linearization

Return type:

LXModel

Returns:

Linearized model

Example

linearized = linearizer.linearize_model() solution = solver.solve(linearized)

get_statistics()

Get linearization statistics.

Return type:

dict

Returns:

Dictionary with counts of linearized terms