10,000 optimal CVRP solutions for testing machine learning based heuristics

Eduardo Queiroga, Ruslan Sadykov, Eduardo Uchoa, Thibaut Vidal

Abstract: We introduce a benchmark of 10,000 instances with heterogeneous characteristics for the capacitated vehicle routing problem. We also provide optimal solutions for almost all of them along with a generator to produce additional training and validation data. This benchmark aims to permit a more systematic comparison of machine learning based search algorithms on this important problem. We also emit recommendations regarding the correct use of this dataset.