New benchmark instances for the Capacitated Vehicle Routing Problem
By Eduardo Uchoa, Diego Pecin, A. Pessoa, M. P. D. Aragão, Thibaut Vidal, Anand Subramanian. European Journal of Operational Research, 2017
558 citations recorded by the source corpus.
The recent research on the CVRP is being slowed down by the lack of a good set of benchmark instances. The existing sets suffer from at least one of the following drawbacks: (i) became too easy for current algorithms; (ii) are too artificial; (iii) are too homogeneous, not covering the wide range of characteristics found in real applications. We propose a new set of 100 instances ranging from 100 to 1000 customers, designed in order to provide a more comprehensive and balanced experimental setting. Moreover, the same generating scheme was also used to provide an extended benchmark of 600 instances. In addition to having a greater discriminating ability to identify “which algorithm is better”, these new benchmarks should also allow for a deeper statistical analysis of the performance of an algorithm. In particular, they will enable one to investigate how the characteristics of an instance affect its performance. We report such an analysis on state-of-the-art exact and heuristic methods.
Subfields: Building and Construction, Industrial and Manufacturing Engineering
View Paper: https://www.semanticscholar.org/paper/b91db36495defb794899ffeae9f2fd4268997489
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Citations in the corpus
- Learning Improvement Heuristics for Solving Routing Problems (2019, methodology): “We further verify that our learned policies, though trained using synthetic data, performs reasonably well on instances from public benchmarks TSPlib 5 [39] and CVRPlib 6 [40], which contains real-world problem instances.”
- Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* Neighborhood (2020, methodology): “Figure 3 illustrates the Swap* neighborhood during one execution of HGS-CVRP on instance X-n101-k25 from Uchoa et al. (2017).”
- A simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times (2019, methodology): “As a benchmark for our test, a set of 27 instances originally proposed by Uchoa et al. (2017) are selected.”