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1570. PyVRP and ICD: Results From the EURO Meets NeurIPS 2022 Vehicle Routing Competition
Invited abstract in session TA-64: Vehicle Routing Under Uncertainty 2, stream VeRoLog - Vehicle Routing and Logistics.
Tuesday, 8:30-10:00Room: S16 (building: 101)
Authors (first author is the speaker)
1. | Leon Lan
|
Vrije Universiteit Amsterdam | |
2. | Niels Wouda
|
University of Groningen | |
3. | Wouter Kool
|
ORTEC | |
4. | Jasper van Doorn
|
Vrije Universiteit Amsterdam | |
5. | Arpan Rijal
|
University of Groningen | |
6. | Sandjai Bhulai
|
Department of Mathematics, Vrije Universiteit Amsterdam |
Abstract
In this talk, we highlight our work that secured first and third place in the EURO Meets NeurIPS 2022 Vehicle Routing Competition on the static and dynamic track, respectively. First, we introduce PyVRP, an open-source and state-of-the-art VRP solver in Python that builds on Thibaut Vidal’s hybrid genetic search algorithm. Through PyVRP, we hope to provide researchers and practitioners the means to build upon a state-of-the-art VRP solver easily and quickly without diving deep into the algorithmic details. Second, we present iterative conditional dispatch (ICD): a simple yet effective algorithm for dynamic vehicle routing problems with stochastic requests. ICD iteratively solves sample scenarios to classify requests to be dispatched, postponed, or undecided. The set of undecided requests shrinks in each iteration until a final dispatching decision is made in the last iteration. A significant strength of ICD is that it is conceptually simple and easy to implement. This simplicity does not harm performance: we show that ICD can nearly match the winning machine learning-based strategy of the EURO Meets NeurIPS 2022 Vehicle Routing Competition. PyVRP and ICD are forthcoming in the INFORMS Journal on Computing and Transportation Science, respectively.
Keywords
- Vehicle Routing
- Software
- Stochastic Models
Status: accepted
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