# PyVRP: a high-performance VRP solver package

arXiv: https://arxiv.org/abs/2403.13795 · HTML: https://mlsanity.com/paper/2403.13795/

## Key facts

- Cited by 52 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 22 Nov 2023.

## Builds on (most cited first, 2 of 2)

- [Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood](https://mlsanity.com/paper/2012.10384/) (2020)
- [Guidelines for the Computational Testing of Machine Learning approaches to Vehicle Routing Problems](https://mlsanity.com/paper/2109.13983/) (2021)

## Built on by (most cited first, 30 of 52)

- [RouteFinder: Towards Foundation Models for Vehicle Routing Problems](https://mlsanity.com/paper/2406.15007/) (2024)
- [Ant Colony Sampling with GFlowNets for Combinatorial Optimization](https://mlsanity.com/paper/2403.07041/) (2024)
- [PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization](https://mlsanity.com/paper/2402.14048/) (2024)
- [Neural Deconstruction Search for Vehicle Routing Problems](https://mlsanity.com/paper/2501.03715/) (2025)
- [Learning to Reduce Search Space for Generalizable Neural Routing Solver](https://mlsanity.com/paper/2503.03137/) (2025)
- [MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver](https://mlsanity.com/paper/2506.02935/) (2025)
- [RRNCO: Towards Real-World Routing with Neural Combinatorial Optimization](https://mlsanity.com/paper/2503.16159/) (2025)
- [URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization](https://mlsanity.com/paper/2509.23413/) (2025)
- [VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems](https://mlsanity.com/paper/2510.07073/) (2025)
- [Multi-Task Vehicle Routing Solver via Mixture of Specialized Experts under State-Decomposable MDP](https://mlsanity.com/paper/2510.21453/) (2025)
- [Neural Genetic Search in Discrete Spaces](https://mlsanity.com/paper/2502.10433/) (2025)
- [An Agentic Framework with LLMs for Solving Complex Vehicle Routing Problems](https://mlsanity.com/paper/2510.16701/) (2025)
- [LMask: Learn to Solve Constrained Routing Problems with Lazy Masking](https://mlsanity.com/paper/2505.17938/) (2025)
- [Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM](https://mlsanity.com/paper/2510.11121/) (2025)
- [AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design](https://mlsanity.com/paper/2605.08756/) (2026)
- [Spatial-temporal-demand clustering for solving large-scale vehicle routing problems with time windows](https://mlsanity.com/paper/2402.00041/) (2024)
- [TuneNSearch: a hybrid transfer learning and local search approach for solving vehicle routing problems](https://mlsanity.com/paper/2503.12662/) (2025)
- [Accelerating Vehicle Routing via AI-Initialized Genetic Algorithms](https://mlsanity.com/paper/2504.06126/) (2025)
- [SVRPBench: A Realistic Benchmark for Stochastic Vehicle Routing Problem](https://mlsanity.com/paper/2505.21887/) (2025)
- [Game-Theoretic Co-Evolution for LLM-Based Heuristic Discovery](https://mlsanity.com/paper/2601.22896/) (2026)
- [Chain-of-Context Learning: Dynamic Constraint Understanding for Multi-Task VRPs](https://mlsanity.com/paper/2603.01667/) (2026)
- [SPACE: Unifying Symmetric and Asymmetric Routing Problems for Generalist Neural Solver](https://mlsanity.com/paper/2605.24484/) (2026)
- [DeepMDV: Global Spatial Matching for Multi-depot Vehicle Routing Problems](https://mlsanity.com/paper/2411.17080/) (2024)
- [USPR: Learning a Unified Solver for Profiled Routing](https://mlsanity.com/paper/2505.05119/) (2025)
- [Recurrent State Encoders for Efficient Neural Combinatorial Optimization](https://mlsanity.com/paper/2509.05084/) (2025)
- [PyVRP^+: LLM-Driven Metacognitive Heuristic Evolution for Hybrid Genetic Search in Vehicle Routing Problems](https://mlsanity.com/paper/2604.07872/) (2026)
- [Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS](https://mlsanity.com/paper/2605.03339/) (2026)
- [Rethinking Constraint Awareness for Efficient State Embedding of Neural Routing Solver](https://mlsanity.com/paper/2605.10122/) (2026)
- [Vision-Assisted Foundation Model for Solving Multi-Task Vehicle Routing Problems](https://mlsanity.com/paper/2606.10431/) (2026)
- [SpecAHD: Localize to Specialize for Automated Heuristic Design in Large-Scale Routing Problems](https://mlsanity.com/paper/2607.23676/) (2026)

## Abstract (arXiv)

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.