Vehicle routing open-source optimization machine (VROOM)

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License: BSD License (BSD 2-Clause License)

Author: Jonathan Feinberg

Requires: Python >=3.7

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Project description

Python Vehicle Routing Open-source Optimization Machine

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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.

Basic usage

>>> 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>

Usage with a routing engine

>>> import vroom

>>> problem_instance = vroom.Input(
...     servers={"auto": "valhalla1.openstreetmap.de:443"},
...     router=vroom._vroom.ROUTER.VALHALLA
... )

>>> problem_instance.add_vehicle(vroom.Vehicle(1, start=(2.44, 48.81), profile="auto"))

>>> problem_instance.add_job([
...     vroom.Job(1, location=(2.44, 48.81)),
...     vroom.Job(2, location=(2.46, 48.7)),
...     vroom.Job(3, location=(2.42, 48.6)),
... ])

>>> sol = problem_instance.solve(exploration_level=5, nb_threads=4)
>>> print(sol.summary.duration)
2698

Installation

Pyvroom currently makes binaries for on macOS and Linux. There is also a Windows build that can be used, but it is somewhat experimental.

Installation of the pre-compiled releases should be as simple as:

pip install pyvroom

Building from source

Building the source distributions requires:

  • Download the Pyvroom repository on you local machine:

    git clone --recurse-submodules https://github.com/VROOM-Project/pyvroom

  • Install the Python dependencies:

    pip install -r pyvroom/build-requirements.txt

  • Install asio headers, and openssl and crypto libraries and headers. On Linux and macOS this involve using package managers like apt, yum or brew. The exact package name may vary a bit between systems.

  • The installation can then be done with:

    pip install pyvroom/

Alternatively it is also possible to install the package from source using Conan. This is also likely the only option if installing on Windows.

To install using Conan, do the following:

cd pyvroom/
conan install --build=openssl --install-folder conan_build .

Documentation

The code is currently only documented with Pydoc. This means that the best way to learn Pyvroom for now is to either look at the source code or use dir() and help() to navigate the interface.

It is also useful to take a look at the VROOM API documentation. The interface there is mostly the same.

Project details

Verified details

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Avatar for jonathf from gravatar.com jonathf

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License: BSD License (BSD 2-Clause License)

Author: Jonathan Feinberg

Requires: Python >=3.7

Classifiers

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