Pré-Publication, Document De Travail Année : 2025

Feature-Guided Metaheuristic with Diversity Management for Solving the Capacitated Vehicle Routing Problem

Résumé

We propose a feature-based guidance mechanism to enhance metaheuristic algorithms for solving the Capacitated Vehicle Routing Problem (CVRP). This mechanism leverages an Explainable AI (XAI) model to identify features that correlate with high-quality solutions. These insights are used to guide the search process by promoting solution diversity and avoiding premature convergence. The guidance mechanism is first integrated into a custom metaheuristic algorithm, which combines neighborhood search with a novel hybrid of the split algorithm and path relinking. Experiments on benchmark instances with up to $30,000$ customer nodes demonstrate that the guidance significantly improves the performance of this baseline algorithm. Furthermore, we validate the generalizability of the guidance approach by integrating it into a state-of-the-art metaheuristic, where it again yields statistically significant performance gains. These results confirm that the proposed mechanism is both scalable and transferable across algorithmic frameworks.

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A comme version hal-05422169 Article Bachtiar Herdianto, Romain Billot, Flavien Lucas, Marc Sevaux. Feature-Guided Metaheuristic with Diversity Management for Solving the Capacitated Vehicle Routing Problem. European Journal of Operational Research, 2025, ⟨10.1016/j.ejor.2025.12.029⟩. ⟨hal-05422169⟩

Accepted to the European Journal of Operations Research

Dates et versions

hal-04663574 , version 1 (29-07-2024)
hal-04663574 , version 2 (20-12-2025)

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Bachtiar Herdianto, Romain Billot, Flavien Lucas, Marc Sevaux. Feature-Guided Metaheuristic with Diversity Management for Solving the Capacitated Vehicle Routing Problem. 2025. ⟨hal-04663574v2⟩
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