The XL Instances for the Capacitated Vehicle Routing Problem
Eduardo Queiroga, Rafael Martinelli, Anand Subramanian, Eduardo Uchoa, Thibaut Vidal
TL;DR
This paper introduces the XL set, a large-scale CVRP benchmark collection spanning 1,000 to 10,000 customers, generated with a principled scheme akin to the X/XML lineage to ensure diverse structural properties. It establishes a CVRPLib Best Known Solution Challenge to propel high-quality initial solutions for the XL instances and conducts extensive experiments with multiple state-of-the-art methods, revealing that AILS-II dominates XL while traditional, population-based methods excel on smaller instances. The work also situates XL within the broader CVRP landscape by analyzing performance across X, XML, and XL, highlighting a shift in effective strategies as problem scale increases. Although the study provides valuable initial baselines, it also notes calibration and methodological limitations, pointing to decomposition and iterative refinement as promising directions for future large-scale CVRP research.
Abstract
This paper introduces a new set of large-scale benchmark instances for the Capacitated Vehicle Routing Problem (CVRP). The proposed XL set extends existing benchmarks by covering instances with 1,000 to 10,000 customers and a wide range of structural characteristics, following established generation principles from prior CVRP studies. A computational study involving several state-of-the-art algorithms is conducted to provide initial best known solutions (BKSs) for the XL instances, which serve as a baseline for a community-driven BKS challenge launched on the CVRPLib website. The instances are made publicly available to support experimental evaluation and comparison of solution methods. Furthermore, additional computational analyses are reported to compare algorithmic performance on other existing CVRP benchmark instances.