discrete_optimization.top.solvers package

Submodules

discrete_optimization.top.solvers.cpsat module

class discrete_optimization.top.solvers.cpsat.CpsatTopSolver(problem: TeamOrienteeringProblem, params_objective_function: ParamsObjectiveFunction | None = None, **kwargs)

Bases: OrtoolsCpSatSolver, WarmstartMixin

init_model(scaling: float = 1, **kwargs: Any) → None

Init cp model and reset stored variables if any.

problem: TeamOrienteeringProblem

retrieve_solution(cpsolvercb: CpSolverSolutionCallback) → VrpSolution

Construct a do solution from the cpsat solver internal solution.

It will be called each time the cpsat solver find a new solution. At that point, value of internal variables are accessible via cpsolvercb.Value(VARIABLE_NAME).

Parameters:

cpsolvercb – the ortools callback called when the cpsat solver finds a new solution.

Returns:

the intermediate solution, at do format.

set_warm_start(solution: VrpSolution, debug_mode: bool = False) → None

Make the solver warm start from the given solution.

discrete_optimization.top.solvers.dp module

class discrete_optimization.top.solvers.dp.DpTopSolver(problem: TeamOrienteeringProblem, params_objective_function: ParamsObjectiveFunction | None = None, **kwargs)

Bases: DpSolver

init_model(scaling: float = 1, **kwargs: Any) → None

Initialize internal model used to solve.

Can initialize a ortools, milp, gurobi, … model.

problem: TeamOrienteeringProblem

retrieve_solution(sol: Solution) → VrpSolution

discrete_optimization.top.solvers.optal module

class discrete_optimization.top.solvers.optal.OptalTopSolver(problem: TeamOrienteeringProblem, params_objective_function: ParamsObjectiveFunction | None = None, **kwargs)

Bases: TopSolver, OptalCpSolver

init_model(scaling: float, **args: Any) → None

Initialize internal model used to solve.

Can initialize a ortools, milp, gurobi, … model.

retrieve_solution(result: cp.SolveResult) → VrpSolution

Return a d-o solution from the variables computed by minizinc.

Parameters:

result – output of the cp.solve

Returns:

discrete_optimization.top.solvers.ortools module

class discrete_optimization.top.solvers.ortools.OrtoolsTopSolver(problem: TeamOrienteeringProblem, params_objective_function: ParamsObjectiveFunction | None = None, **kwargs: Any)

Bases: SolverDO

build_search_parameters(**kwargs: Any) → RoutingSearchParameters

init_model(scaling: float = 1, **kwargs: Any) → None

Initialize internal model used to solve.

Can initialize a ortools, milp, gurobi, … model.

manager: RoutingIndexManager | None = None

problem: TeamOrienteeringProblem

routing: RoutingModel | None = None

solve(callbacks: list[Callback] | None = None, time_limit: int = 100, **kwargs: Any) → ResultStorage

Generic solving function.

Parameters:

• callbacks – list of callbacks used to hook into the various stage of the solve

• **kwargs – any argument specific to the solver

Solvers deriving from SolverDo should use callbacks methods .on_step_end(), … during solve(). But some solvers are not yet updated and are just ignoring it.

Returns (ResultStorage): a result object containing potentially a pool of solutions to a discrete-optimization problem

class discrete_optimization.top.solvers.ortools.TopRoutingMonitor(do_solver: OrtoolsTopSolver, callback: Callback)

Bases: SearchMonitor

Monitor to retrieve intermediate solutions and handle callbacks (logging, early stopping) for the Team Orienteering Problem.

AtSolution() → bool

Called by OR-Tools whenever a valid solution is found.

EnterSearch()

Beginning of the search.

ExitSearch()

End of the search.

retrieve_current_solution() → None

Converts the current OR-Tools assignment to a VrpSolution.

Module contents

class discrete_optimization.top.solvers.TopSolver(problem: TeamOrienteeringProblem, params_objective_function: ParamsObjectiveFunction | None = None, **kwargs)

Bases: SolverDO

problem: TeamOrienteeringProblem