Publication Type
Journal Article
Version
acceptedVersion
Publication Date
8-2021
Abstract
The Vehicle Routing Problem (VRP) was formally presented to the scientific literature in 1959 by Dantzig and Ramser (DOI:10.1287/mnsc.6.1.80). Sixty years on, the problem is still heavily researched, with hundreds of papers having been published addressing this problem and the many variants that now exist. Many datasets have been proposed to enable researchers to compare their algorithms using the same problem instances where either the best known solution is known or, in some cases, the optimal solution is known. In this survey paper, we provide a list of Vehicle Routing Problem datasets, categorized to enable researchers to have easy access to the problem(s) that are of interest. We also make some suggestions as to the type of datasets that might be useful in the future in order to provide the scientific community with even more challenging problems, which are suited to the problems that we face today. This paper, as well as providing a list of benchmarks, also provides a checkpoint for the scientific community so that other researchers have an opportunity of comparing the growth of VRP instances that are available.
Keywords
Vehicle routing, VRP, datasets
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing | Operations Research, Systems Engineering and Industrial Engineering
Research Areas
Intelligent Systems and Optimization
Publication
Journal of the Operational Research Society
Volume
72
Issue
8
First Page
1794
Last Page
1807
ISSN
0160-5682
Identifier
10.1080/01605682.2021.1884505
Publisher
Taylor and Francis
Embargo Period
2-18-2022
Citation
GUNAWAN, Aldy; KENDALL, Graham; McCollum, Barry; SEOW, Hsin-Vonn; and LEE, Lai Soon.
Vehicle routing: Review of benchmark datasets. (2021). Journal of the Operational Research Society. 72, (8), 1794-1807.
Available at: https://ink.library.smu.edu.sg/sis_research/6037
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/01605682.2021.1884505
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons