BigVRSP: A Data-Driven Instance Generator for Long-Haul Vehicle Routing and Scheduling Problems

André Felipe Zanella; Fabrício Faneco Júnior; Guilherme Philippi; Pedro Rochavetz de Lara Andrade; Emerson Vitor Castelani; Francisco Nogueira Calmon Sobral; Rafael Henrique Palma Lima; Gislaine Camila Lapasini Leal

doi:10.5334/jors.694

BigVRSP: A Data-Driven Instance Generator for Long-Haul Vehicle Routing and Scheduling Problems

Volume 14 (2026): Issue 1

By: André Felipe Zanella , Fabrício Faneco Júnior , Guilherme Philippi , Pedro Rochavetz de Lara Andrade , Emerson Vitor Castelani , Francisco Nogueira Calmon Sobral , Rafael Henrique Palma Lima and Gislaine Camila Lapasini Leal

Open Access

|Sep 2026

Abstract

This paper introduces BigVRSP, an instance generator tool for long-haul transportation problems, designed to support numerical experiments in real-life pickup and delivery and truck assignment applications. The software automates the process of building realistic scenarios by combining either historical operational data or artificially generated ones with user preferences through command-line interface (CLI) parameters. Implemented as a series of Python scripts with CLI, it generates structured text datasets as CSV files, for both trucks and customer requests. The tool is openly available in a public repository on Gitlab and can be easily integrated into workflows in many different logistics contexts.

References

Gunawan A, Kendall G, McCollum B, Seow HV, Lee LS. Vehicle routing: Review of benchmark datasets. Journal of the Operational Research Society. 2021;72(8):1794–1807. DOI: 10.1080/01605682.2021.1884505
Open DOI Search in Google Scholar Back to article
Simeonova L, Wassan N, Salhi S, Nagy G. The heterogeneous fleet vehicle routing problem with light loads and overtime: Formulation and population variable neighbourhood search with adaptive memory. Expert Systems with Applications. 2018;114:183–195. DOI: 10.1016/j.eswa.2018.07.034
Open DOI Search in Google Scholar Back to article
Queiroz M, Lucas F, Sörensen K. Instance generation tool for on-demand transportation problems. European Journal of Operational Research. 2024;317(3):696–717. DOI: 10.1016/j.ejor.2024.03.006
Open DOI Search in Google Scholar Back to article
Akbay MA, Blum C. EVRPGen: A web-based instance generator for the electric vehicle routing problem with road junctions and road types. Software Impacts. 2025;25:100778. DOI: 10.1016/j.simpa.2025.100778
Open DOI Search in Google Scholar Back to article
Diaz Urra R, Galvez Ramirez N, Castro C. A framework for the generation of complex scenario instances in the Urban Transit Routing Problem. Annals of Mathematics and Artificial Intelligence. 2023;91(2):153–175. DOI: 10.1007/s10472-022-09797-z
Open DOI Search in Google Scholar Back to article
Lucci M, Severín D, Zabala P. Exact resolution of a simultaneous vehicle routing and crew scheduling problem in long-haul transport. International Transactions in Operational Research; 2026;33(5):3158–3186. DOI: 10.1111/itor.70014
Open DOI Search in Google Scholar Back to article
Parragh SN, Doerner KF, Hartl RF. A survey on pickup and delivery problems. Journal für Betriebswirtschaft. 2008;58: 21–51. DOI: 10.1007/s11301-008-0033-7
Open DOI Search in Google Scholar Back to article
Parragh SN, Doerner KF, Hartl RF. A survey on pickup and delivery problems. Journal für Betriebswirtschaft. 2008;58:81–117. DOI: 10.1007/s11301-008-0036-4
Open DOI Search in Google Scholar Back to article
Gronalt M, Hirsch P. Log-Truck Scheduling with a Tabu Search Strategy. In: Doerner KF, Gendreau M, Greistorfer P, Gutjahr W, Hartl RF, Reimann M, editors. Metaheuristics. Operations Research/Computer Science Interfaces Series, vol. 39. Boston, MA: Springer, pp. 65–88; 2007. DOI: 10.1007/978-0-387-71921-4_4
Open DOI Search in Google Scholar Back to article
Soares R, Marques A, Amorim P, Rasinmäki, J. Multiple vehicle synchronisation in a full truck-load pickup and delivery problem: A case-study in the biomass supply chain. European Journal of Operational Research. 2019;277:174–194. DOI: 10.1016/j.ejor.2019.02.025
Open DOI Search in Google Scholar Back to article
Vidal T, Crainic TG, Gendreau M, Prins, C. Heuristics for multi-attribute vehicle routing problems: A survey and synthesis. European Journal of Operational Research. 2013;231:1–21. DOI: 10.1016/j.ejor.2013.02.053
Open DOI Search in Google Scholar Back to article

Articles in this issue

DOI: https://doi.org/10.5334/jors.694 | Journal eISSN: 2049-9647

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Language: English

Page range: 62 - 62

Submitted on: Feb 11, 2026

Accepted on: Sep 3, 2026

Published on: Sep 23, 2026

Published by: Ubiquity Press

In partnership with: Paradigm Publishing Services

Keywords:

long-haul transportation,

© 2026 André Felipe Zanella, Fabrício Faneco Júnior, Guilherme Philippi, Pedro Rochavetz de Lara Andrade, Emerson Vitor Castelani, Francisco Nogueira Calmon Sobral, Rafael Henrique Palma Lima, Gislaine Camila Lapasini Leal, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 14 (2026): Issue 1