This paper investigates the multi-compartment vehicle routing problem with multiple time windows (MCVRPMTW), an extension of the classical vehicle routing problem with time windows that considers vehicles equipped with multiple compartments and customers requiring service across several delivery time windows. The problem incorporates three key compartment-related features: (i) compartment flexibility in the number of compartments, (ii) item-to-compartment compatibility, and (iii) item-to-item compatibility. The problem also accommodates practical operational requirements such as driver breaks. To solve the MCVRPMTW, we develop an exact branch-and-price (B&P) algorithm in which the pricing problem is solved using a labeling algorithm. Several acceleration strategies are introduced to limit symmetry during label extensions, improve the stability of dual solutions in column generation, and enhance the branching process. To handle large-scale instances, we propose a rolling-space B&P algorithm that integrates clustering techniques into the solution framework. Extensive computational experiments on instances inspired by a real-world industrial application demonstrate the effectiveness of the proposed approach and provide useful managerial insights for practical implementation.

翻译：本文研究了具有多时间窗的多隔间车辆路径问题，该问题是经典带时间窗车辆路径问题的扩展，考虑了配备多个隔间的车辆以及需要在多个配送时间窗内接受服务的客户。该问题包含三个关键的隔间相关特征：(i) 隔间数量的灵活性，(ii) 物品与隔间的兼容性，以及(iii) 物品与物品的兼容性。该问题还考虑了驾驶员休息等实际运营需求。为求解该问题，我们开发了一种精确的分支定价算法，其中定价问题通过标签算法求解。我们引入了多种加速策略，以限制标签扩展过程中的对称性、提高列生成中对偶解的稳定性，并改进分支过程。为处理大规模算例，我们提出了一种滚动空间分支定价算法，将聚类技术集成到求解框架中。基于实际工业应用启发的算例进行的广泛计算实验证明了所提方法的有效性，并为实际应用提供了有用的管理启示。