Good solution, fast... in Python.
Pyvroom is an Python wrapper to the excellent VROOM optimization engine for solving vehicle routing problems.
The library aims to solve several well-known types of vehicle routing problems, including:
- Travelling salesman.
- Capacitated vehicle routing.
- Routing with time windows.
- Multi-depot heterogeneous vehicle.
- Pickup-and-delivery.
VROOM can also solve any mix of the above problem types.
Pyvroom currently makes binaries for on MacOS and Linux (Windows is WIP).
Installation should be as simple as:
pip install pyvroomBuilding the source distributions on another OS requires:
- the
./build-requirements.txtPython dependencies asioheaders installedopenssl&cryptolibraries & headers installed
Optionally the C++ dependencies can be installed with conan:
conan install --build=openssl --install-folder conan_build .>>> import vroom
>>> problem_instance = vroom.Input()
>>> problem_instance.set_durations_matrix(
... profile="car",
... matrix_input=[[0, 2104, 197, 1299],
... [2103, 0, 2255, 3152],
... [197, 2256, 0, 1102],
... [1299, 3153, 1102, 0]],
... )
>>> problem_instance.add_vehicle([vroom.Vehicle(47, start=0, end=0),
... vroom.Vehicle(48, start=2, end=2)])
>>> problem_instance.add_job([vroom.Job(1414, location=0),
... vroom.Job(1515, location=1),
... vroom.Job(1616, location=2),
... vroom.Job(1717, location=3)])
>>> solution = problem_instance.solve(exploration_level=5, nb_threads=4)
>>> solution.summary.cost
6411
>>> solution.routes.columns
Index(['vehicle_id', 'type', 'arrival', 'duration', 'setup', 'service',
'waiting_time', 'location_index', 'id', 'description'],
dtype='object')
>>> solution.routes[["vehicle_id", "type", "arrival", "location_index", "id"]]
vehicle_id type arrival location_index id
0 47 start 0 0 <NA>
1 47 job 2104 1 1515
2 47 job 4207 0 1414
3 47 end 4207 0 <NA>
4 48 start 0 2 <NA>
5 48 job 1102 3 1717
6 48 job 2204 2 1616
7 48 end 2204 2 <NA>