discrete_optimization.shop.transformations package

Submodules

discrete_optimization.shop.transformations.to_generic_scheduling module

Transformation from CommonShopProblem (JSP/FJSP/OSP) to GenericSchedulingImpl.

class discrete_optimization.shop.transformations.to_generic_scheduling.ShopToGenericSchedulingTransformation[source]

Bases: ProblemTransformation[CommonShopProblem, AnyShopSolution, GenericSchedulingImplProblem, GenericSchedulingImplSolution]

Transform CommonShopProblem to GenericSchedulingImplProblem.

This transformation works for JSP, FJSP, and OSP problems: - JSP: Single mode per task (one recipe per subjob) - FJSP: Multiple modes per task (multiple recipe options per subjob) - OSP: Single mode per task, no precedence constraints

Mapping: - Tasks: (job_index, subjob_index) tuples - Modes: Recipe options for each subjob - Cumulative resources: Machines (capacity 1 each) - Precedence: From problem’s get_precedence_constraints() - No-overlap: Tasks within same job (from get_no_overlap())

back_transform_solution(solution: GenericSchedulingImplSolution, source_problem: CommonShopProblem) → AnyShopSolution[source]

Transform GenericSchedulingImplSolution back to CommonShopProblem solution.

Parameters:

  • solution – GenericSchedulingImplSolution

  • source_problem – Original CommonShopProblem

Returns:

Equivalent CommonShopProblem solution

forward_transform_solution(solution: AnyShopSolution, target_problem: GenericSchedulingImplProblem) → GenericSchedulingImplSolution | None[source]

Transform CommonShopProblem solution to GenericSchedulingImplSolution.

Parameters:

  • solution – CommonShopProblem solution

  • target_problem – Target GenericSchedulingImplProblem

Returns:

Equivalent GenericSchedulingImplSolution for warm-start

transform_problem(source_problem: CommonShopProblem) → GenericSchedulingImplProblem[source]

Transform CommonShopProblem to GenericSchedulingImplProblem.

Parameters:

source_problem – CommonShopProblem instance (JSP/FJSP/OSP)

Returns:

Equivalent GenericSchedulingImplProblem

discrete_optimization.shop.transformations.to_rcpsp_multimode module

Transformation from CommonShopProblem (JSP/FJSP/OSP) to multimode RCPSP.

class discrete_optimization.shop.transformations.to_rcpsp_multimode.ShopToRcpspMultimodeTransformation[source]

Bases: ProblemTransformation[CommonShopProblem, AnyShopSolution, RcpspProblem, RcpspSolution]

Transform CommonShopProblem to multimode RCPSP.

This transformation works for JSP, FJSP, and OSP problems: - JSP: Single mode per task (one recipe per subjob) - FJSP: Multiple modes per task (multiple recipe options per subjob) - OSP: Single mode per task, no precedence constraints

Mapping: - (job_j, subjob_k) → task_{j}_{k} - Recipe options → modes for each task - Machines → renewable resources (capacity 1) - Processing time on machine → duration for that mode - Job precedence + no-overlap constraints → task successors and constraints

back_transform_solution(solution: RcpspSolution, source_problem: CommonShopProblem) → AnyShopSolution[source]

Transform RCPSP solution back to CommonShopProblem solution.

Parameters:

  • solution – RCPSP solution

  • source_problem – Original CommonShopProblem

Returns:

Equivalent CommonShopProblem solution

forward_transform_solution(solution: AnyShopSolution, target_problem: RcpspProblem) → RcpspSolution | None[source]

Transform CommonShopProblem solution to RCPSP solution (for warm-start).

Parameters:

  • solution – CommonShopProblem solution

  • target_problem – Target RCPSP problem

Returns:

Equivalent RCPSP solution for warm-start

transform_problem(source_problem: CommonShopProblem) → RcpspProblem[source]

Transform CommonShopProblem to multimode RCPSP.

Parameters:

source_problem – CommonShopProblem instance (JSP/FJSP/OSP)

Returns:

Equivalent multimode RCPSP problem

Module contents