ml4co_kit.task.routing.vrp.cvrpl

Capacitated Vehicle Routing Problem with length limit (CVRPL).

CVRPL extends CVRP by requiring every vehicle route to satisfy a maximum route length constraint.

Classes

CVRPLTask(cvrp_open, distance_type, ...)

class ml4co_kit.task.routing.vrp.cvrpl.CVRPLTask(cvrp_open: bool = False, distance_type: ~ml4co_kit.task.routing.base.DISTANCE_TYPE = DISTANCE_TYPE.EUC_2D, round_type: ~ml4co_kit.task.routing.base.ROUND_TYPE = ROUND_TYPE.NO, precision: ~numpy.float32 | ~numpy.float64 = <class 'numpy.float32'>, threshold: float = 0.0001)[source]

Bases: CVRPTask

check_constraints(sol: ndarray) → bool[source]: Check if the solution is valid.

from_data(depots: ndarray = None, points: ndarray = None, demands: ndarray = None, capacity: float = None, max_route_length: float = None, sol: ndarray = None, ref: bool = False, normalize: bool = False, name: str = None)[source]

Populate the task from numpy arrays.

Parameters

depotsnp.ndarray, optional: Depot coordinates, shape (2,) or (3,).
pointsnp.ndarray, optional: Customer coordinates, shape (V, 2) or (V, 3).
demandsnp.ndarray, optional: Customer demands, shape (V,).
capacityfloat, optional: Vehicle capacity.
solnp.ndarray, optional: Tour encoding with 0 depot delimiters.
refbool, optional: If True, store sol in ref_sol instead of sol.
normalizebool, optional: Scale coordinates to [0, 1] (EUC_2D only).
namestr, optional: Instance name override.