PyVRP: A High-Performance VRP Solver Package

Niels A. Wouda (), Leon Lan () and Wouter Kool ()
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Niels A. Wouda: Department of Operations, University of Groningen, 9747 AE Groningen, Netherlands
Leon Lan: Department of Mathematics, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands
Wouter Kool: ORTEC, 2719 EA Zoetermeer, Netherlands

INFORMS Journal on Computing, 2024, vol. 36, issue 4, 943-955

Abstract: 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 customizable at the Python level. PyVRP is a polished implementation of the algorithm that ranked first in the 2021 DIMACS VRPTW challenge and, after improvements, ranked first 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.There is a video associated with this paper. Click here to view the Video Overview . To save the file, right click and choose “Save Link As” from the menu.

Keywords: vehicle routing problem; time windows; hybrid genetic search; open source; C++; Python (search for similar items in EconPapers)
Date: 2024
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