rosomaxa

A Vehicle Routing Problem solver

https://github.com/reinterpretcat/vrp

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (19.1%) to scientific vocabulary

Keywords

logistics-planning-problem rich-vrp transportation-planning traveling-salesman-problem vehicle-routing-problem vrp vrp-solver
Last synced: 6 months ago · JSON representation ·

Repository

A Vehicle Routing Problem solver

Basic Info
Statistics
  • Stars: 437
  • Watchers: 28
  • Forks: 84
  • Open Issues: 45
  • Releases: 54
Topics
logistics-planning-problem rich-vrp transportation-planning traveling-salesman-problem vehicle-routing-problem vrp vrp-solver
Created about 6 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License Citation

README.md

crates.io build downloads codecov CodeScene Code Health dependency status DOI

VRP example

Description

This project provides a way to solve multiple variations of Vehicle Routing Problem known as rich VRP. It provides custom hyper- and meta-heuristic implementations, shortly described here.

If you use the project in academic work, please consider citing:

@misc{builuk_rosomaxa_2023, author = {Ilya Builuk}, title = {{A new solver for rich Vehicle Routing Problem}}, year = 2023, doi = {10.5281/zenodo.4624037}, publisher = {Zenodo}, url = {https://doi.org/10.5281/zenodo.4624037} }

Design goal

Although performance is constantly in focus, the main idea behind design is extensibility: the project aims to support a wide range of VRP variations known as Rich VRP. This is achieved through various extension points: custom constraints, objective functions, acceptance criteria, etc.

Getting started

For general installation steps and basic usage options, please check the next sections. More detailed overview of the features and full description of the usage is presented in A Vehicle Routing Problem Solver Documentation.

Probably, the easiest way to learn how to use the solver as is, would be to play with interactive tutorial, written as jupyter notebook.

Additionally, you can check vrp-core/examples to see how to use the library and extend it within a new functionality.

Installation

You can install the latest release of the vrp solver using four different ways:

Install with Python

The functionality of vrp-cli is published to pypi.org, so you can just install it using pip and use from python:

shell pip install vrp-cli python examples/python-interop/example.py # run test example

Alternatively, you can use maturin tool to build solver locally. You need to enable py_bindings feature which is not enabled by default.

Additionally, to jupyter notebook mentioned above, you can find extra information in python example section of the docs. The full source code of python example is available in the repo which contains useful model wrappers with help of pydantic lib (reused by tutorial as well).

Install from Docker

Another fast way to try vrp solver on your environment is to use docker image (not performance optimized):

  • run public image from Github Container Registry:

bash docker run -it -v $(pwd):/repo --name vrp-cli --rm ghcr.io/reinterpretcat/vrp/vrp-cli:1.25.0

  • build image locally using Dockerfile provided:

bash docker build -t vrp_solver . docker run -it -v $(pwd):/repo --rm vrp_solver

Please note that the docker image is built using musl, not glibc standard library. So there might be some performance implications.

Install from Cargo

You can install vrp solver cli tool directly with cargo install:

cargo install vrp-cli

Ensure that your $PATH is properly configured to source the crates binaries, and then run solver using the vrp-cli command.

Install from source

Once pulled the source code, you can build it using cargo:

cargo build --release

Built binaries can be found in the ./target/release directory and can be run using vrp-cli executable, e.g.:

./target/release/vrp-cli solve solomon examples/data/scientific/solomon/C101.100.txt --log

Alternatively, you can try to run the following script from the project root (with pragmatic format only):

./solve_problem.sh examples/data/pragmatic/objectives/berlin.default.problem.json

It will build the executable and automatically launch the solver with the specified VRP definition. Results are stored in the folder where a problem definition is located.

Please note, that master branch normally contains not yet released changes.

Usage

Using from code

If you're using rust, you have multiple options for how the project can be used:

Use customization capabilities

The vrp-core provides API to compose a VRP formulation from various building blocks and even add your own. Start with basic vrp-core/examples, then check the user documentation and code for more details.

Use built-in formats

You can use vrp-scientific, vrp-pragmatic crates to solve a VRP problem defined in pragmatic or scientific format using default metaheuristic. Or you can use CLI interface for that (see below).

If you're using some other language, e.g. java, kotlin, javascript, python, please check interop section in documentation examples to see how to call the library from it (currently, limited to pragmatic format).

Using from command line

vrp-cli crate is designed to use on problems defined in scientific or custom json (aka pragmatic) format:

vrp-cli solve pragmatic problem_definition.json -m routing_matrix.json --max-time=120

Please refer to getting started section in the documentation for more details.

Contribution policy

open source, limited contribution

The goal is to reduce burnout by limiting the maintenance overhead of reviewing and validating third-party code.

Please submit an issue or discussion if you have ideas for improvement.

Status

Permanently experimental. This is my pet project, and I'm not paid for it, so expect a very limited support.

Owner

  • Name: Ilya Builuk
  • Login: reinterpretcat
  • Kind: user
  • Location: Berlin, Germany

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Builuk"
  given-names: "Ilya"
  orcid: "https://orcid.org/0000-0002-7613-7412"
title: "Rosomaxa, Vehicle Routing Problem Solver"
version: 1.25.0
doi: 10.5281/zenodo.4624037
date-released: 2024-07-13
url: "https://github.com/reinterpretcat/vrp"

GitHub Events

Total
  • Create event: 9
  • Issues event: 4
  • Release event: 2
  • Watch event: 72
  • Delete event: 3
  • Issue comment event: 14
  • Push event: 121
  • Pull request event: 5
  • Fork event: 13
Last Year
  • Create event: 9
  • Issues event: 4
  • Release event: 2
  • Watch event: 72
  • Delete event: 3
  • Issue comment event: 14
  • Push event: 121
  • Pull request event: 5
  • Fork event: 13

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 3,029
  • Total Committers: 5
  • Avg Commits per committer: 605.8
  • Development Distribution Score (DDS): 0.001
Past Year
  • Commits: 257
  • Committers: 1
  • Avg Commits per committer: 257.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
reinterpretcat i****k@g****m 3,025
pryborg 1****g 1
ibrahim ethem demirci d****r@h****m 1
andrewgy8 a****8@g****m 1
Sebastian vdH s****f@h****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 114
  • Total pull requests: 14
  • Average time to close issues: 3 months
  • Average time to close pull requests: 14 days
  • Total issue authors: 56
  • Total pull request authors: 11
  • Average comments per issue: 3.09
  • Average comments per pull request: 1.0
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 5
  • Pull requests: 4
  • Average time to close issues: 3 days
  • Average time to close pull requests: about 2 hours
  • Issue authors: 4
  • Pull request authors: 3
  • Average comments per issue: 0.8
  • Average comments per pull request: 0.75
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 1
Top Authors
Issue Authors
  • reinterpretcat (11)
  • pierrethiriet (7)
  • ilibar-zpt (6)
  • tdeenes (6)
  • iedmrc (4)
  • KhDenys (4)
  • xeroxstar (4)
  • K-Leon (3)
  • leobudima (3)
  • wesleimp (3)
  • skyien (3)
  • nkl1996 (3)
  • dooley (2)
  • neemanjabu (2)
  • aaronzberger (2)
Pull Request Authors
  • akitaylor (3)
  • blaggacao (3)
  • AngryAntoine (2)
  • dependabot[bot] (2)
  • rbilgil (1)
  • iedmrc (1)
  • andrewgy8 (1)
  • shvandehoef (1)
  • aloksuresh-peakai (1)
  • wesleimp (1)
  • cnpryer (1)
Top Labels
Issue Labels
enhancement (8) bug (8) pragmatic (2) documentation (1)
Pull Request Labels
dependencies (2)

Packages

  • Total packages: 7
  • Total downloads:
    • cargo 404,275 total
    • pypi 162 last-month
  • Total dependent packages: 9
    (may contain duplicates)
  • Total dependent repositories: 6
    (may contain duplicates)
  • Total versions: 338
  • Total maintainers: 2
crates.io: vrp-core

A core algorithms to solve a Vehicle Routing Problem

  • Versions: 77
  • Dependent Packages: 4
  • Dependent Repositories: 2
  • Downloads: 96,384 Total
Rankings
Dependent packages count: 6.4%
Forks count: 8.8%
Stargazers count: 9.8%
Average: 9.9%
Downloads: 10.6%
Dependent repos count: 13.7%
Maintainers (1)
Last synced: 6 months ago
crates.io: vrp-pragmatic

An extension logic for solving rich VRP

  • Versions: 77
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 94,134 Total
Rankings
Forks count: 8.8%
Stargazers count: 9.8%
Downloads: 10.9%
Average: 11.8%
Dependent repos count: 13.7%
Dependent packages count: 15.7%
Maintainers (1)
Last synced: 6 months ago
crates.io: vrp-scientific

An extension logic for solving scientific VRP

  • Versions: 77
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 90,154 Total
Rankings
Forks count: 8.8%
Stargazers count: 9.8%
Downloads: 11.5%
Average: 12.6%
Dependent packages count: 15.7%
Dependent repos count: 17.1%
Maintainers (1)
Last synced: 6 months ago
crates.io: vrp-cli

A command line interface for VRP solver

  • Versions: 77
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 88,805 Total
Rankings
Forks count: 8.8%
Stargazers count: 9.8%
Downloads: 11.7%
Average: 15.7%
Dependent repos count: 17.1%
Dependent packages count: 31.2%
Maintainers (1)
Last synced: 6 months ago
crates.io: rosomaxa

A rosomaxa algorithm and other building blocks for creating a solver for optimization problems

  • Versions: 18
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 29,797 Total
Rankings
Forks count: 9.0%
Stargazers count: 10.3%
Dependent packages count: 17.0%
Average: 17.1%
Downloads: 20.1%
Dependent repos count: 29.3%
Maintainers (1)
Last synced: 6 months ago
pypi.org: vrp-cli

A command line interface for VRP solver

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 162 Last month
Rankings
Stargazers count: 4.3%
Forks count: 6.2%
Dependent packages count: 6.6%
Average: 19.9%
Dependent repos count: 30.6%
Downloads: 51.8%
Maintainers (1)
Last synced: 6 months ago
crates.io: vrp-solver

An extension which provides custom metaheuristic for solving VRP

  • Versions: 4
  • Dependent Packages: 2
  • Dependent Repositories: 0
  • Downloads: 5,001 Total
Rankings
Forks count: 9.0%
Stargazers count: 10.3%
Dependent packages count: 11.4%
Average: 20.7%
Dependent repos count: 29.3%
Downloads: 43.7%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/audit.yaml actions
  • actions-rs/audit-check v1 composite
  • actions/checkout v1 composite
.github/workflows/build.yaml actions
  • actions-rs/cargo v1 composite
  • actions/checkout v2 composite
  • actions/upload-artifact v2 composite
.github/workflows/coverage.yaml actions
  • actions-rs/tarpaulin v0.1 composite
  • actions-rs/toolchain v1 composite
  • actions/checkout v2 composite
  • actions/upload-artifact v1 composite
  • codecov/codecov-action v1.0.2 composite
.github/workflows/discovery.yaml actions
  • actions/checkout v2 composite
.github/workflows/experiments.yaml actions
  • actions-rs/toolchain v1 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • actions/upload-artifact v2 composite
.github/workflows/maturin.yaml actions
  • PyO3/maturin-action v1 composite
  • actions/checkout v3 composite
  • actions/download-artifact v3 composite
  • actions/setup-python v4 composite
  • actions/upload-artifact v3 composite
.github/workflows/publish.yaml actions
  • actions/checkout v2 composite
  • actions/create-release v1 composite
  • actions/upload-release-asset v1 composite
  • docker/build-push-action v1 composite
  • montudor/action-zip v0.1.0 composite
Cargo.toml cargo
examples/json-pragmatic/Cargo.toml cargo
  • criterion 0.5.1 development
experiments/heuristic-research/Cargo.toml cargo
rosomaxa/Cargo.toml cargo
vrp-cli/Cargo.toml cargo
  • tempfile 3.8.0 development
  • csv 1.2.2
vrp-core/Cargo.toml cargo
vrp-pragmatic/Cargo.toml cargo
  • proptest 1.2.0 development
  • uuid 1.4.1 development
  • time 0.3.28
vrp-scientific/Cargo.toml cargo
Dockerfile docker
  • alpine 3.16 build
  • rust 1.72-alpine build
examples/jvm-interop/build.gradle maven
  • net.java.dev.jna:jna 5.2.0 implementation
  • org.jetbrains.kotlin:kotlin-stdlib-jdk8 * implementation
vrp-cli/pyproject.toml pypi