discrete_optimization.shop.fjsp package

Subpackages

• discrete_optimization.shop.fjsp.solvers package
  • Submodules
  • discrete_optimization.shop.fjsp.solvers.cpsat module
  • discrete_optimization.shop.fjsp.solvers.dp module
    • DpFjspSolver
      • DpFjspSolver.hyperparameters
      • DpFjspSolver.init_model()
      • DpFjspSolver.problem
      • DpFjspSolver.retrieve_solution()
      • DpFjspSolver.set_warm_start()
  • discrete_optimization.shop.fjsp.solvers.lns_cpsat module
    • FjspConstraintHandler
      • FjspConstraintHandler.adding_constraint_from_results_store()
    • NeighFjspConstraintHandler
      • NeighFjspConstraintHandler.adding_constraint_from_results_store()
    • NeighborBuilderSubPart
      • NeighborBuilderSubPart.find_subtasks()
  • discrete_optimization.shop.fjsp.solvers.optal module
    • OptalFJspSolver
      • OptalFJspSolver.get_task_interval_variable()
      • OptalFJspSolver.init_model()
      • OptalFJspSolver.problem
      • OptalFJspSolver.retrieve_solution()
  • Module contents
• discrete_optimization.shop.fjsp.transformations package
  • Submodules
  • discrete_optimization.shop.fjsp.transformations.to_rcpsp module
    • FjspToRcpspTransformation
      • FjspToRcpspTransformation.back_transform_solution()
      • FjspToRcpspTransformation.forward_transform_solution()
      • FjspToRcpspTransformation.transform_problem()
  • discrete_optimization.shop.fjsp.transformations.to_workforce module
    • FjspToWorkforceSchedulingTransformation
      • FjspToWorkforceSchedulingTransformation.back_transform_solution()
      • FjspToWorkforceSchedulingTransformation.forward_transform_solution()
      • FjspToWorkforceSchedulingTransformation.get_forward_metadata()
      • FjspToWorkforceSchedulingTransformation.transform_problem()
  • Module contents
    • FjspToRcpspTransformation
      • FjspToRcpspTransformation.back_transform_solution()
      • FjspToRcpspTransformation.forward_transform_solution()
      • FjspToRcpspTransformation.transform_problem()
    • FjspToWorkforceSchedulingTransformation
      • FjspToWorkforceSchedulingTransformation.back_transform_solution()
      • FjspToWorkforceSchedulingTransformation.forward_transform_solution()
      • FjspToWorkforceSchedulingTransformation.get_forward_metadata()
      • FjspToWorkforceSchedulingTransformation.transform_problem()

Submodules

discrete_optimization.shop.fjsp.parser module

discrete_optimization.shop.fjsp.parser.get_data_available(data_folder: str | None = None, data_home: str | None = None) → list[str]

Get datasets available for jobshop.

discrete_optimization.shop.fjsp.parser.parse_file(file_path: str)

discrete_optimization.shop.fjsp.problem module

class discrete_optimization.shop.fjsp.problem.FJobShopProblem(list_jobs: list[Job], n_jobs: int = None, n_machines: int = None, horizon: int = None)

Bases: CommonShopProblem

get_last_tasks() → list[tuple[int, int]]

Get a sublist of tasks that are candidate to be the last one scheduled.

Default to all tasks.

get_precedence_constraints() → dict[tuple[int, int], list[tuple[int, int]]]

Map each task to the tasks that need to be performed after it.

get_resource_availabilities(resource: int) → list[tuple[int, int, int]]

Get availabilities intervals for a given resource

List of availability intervals of a resource. If the resource is not available, potentially no interval returned.

It is assumed that the intervals are disjunct though.

Parameters:

resource

Returns:

list of intervals of the form (start, end, value), which means from time start to time end, there are value of the resource available. NB: the start is included, the end is excluded (start <= t < end)

Module contents