Papers › PyVRP: a high-performance VRP solver package

PyVRP: a high-performance VRP solver package

22 Nov 2023arXiv:2403.13795archive 2025-07-28

Niels A. Wouda, Leon Lan, Wouter Kool

We introduce PyVRP, a Python package that implements hybrid genetic search in a state-of-the-art vehicle routing problem (VRP) solver. The package is designed for the VRP with time windows (VRPTW), but can be easily extended to support other VRP variants. PyVRP combines the flexibility of Python with the performance of C++, by implementing (only) performance critical parts of the algorithm in C++, while being fully customisable at the Python level. PyVRP is a polished implementation of the algorithm that ranked 1st in the 2021 DIMACS VRPTW challenge and, after improvements, ranked 1st on the static variant of the EURO meets NeurIPS 2022 vehicle routing competition. The code follows good software engineering practices, and is well-documented and unit tested. PyVRP is freely available under the liberal MIT license. Through numerical experiments we show that PyVRP achieves state-of-the-art results on the VRPTW and capacitated VRP. We hope that PyVRP enables researchers and practitioners to easily and quickly build on a state-of-the-art VRP solver.

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pyvrp/pyvrp officialmentioned in papermentioned on GitHubMIT report
informsjoc/2023.0055 officialmentioned in paperMIT report

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cumsum Valdecy/pyVRP/tests/test_evaluate_distance.py community ran · violated contract fingerprinted no licence file found · pointer only · 84c0d42a93002d4e · report
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build_distance_matrix Valdecy/pyVRP/src/pyVRP.py community unverified no licence file found · pointer only · fb81c15676c61a73 · report

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