Autonomous mobile robots (AMRs) are increasingly used to automate operations in intralogistics. One crucial feature of AMRs is their availability, allowing them to operate 24/7. This work addresses the multibay unit load pre-marshalling problem, which extends pre-marshalling from a single bay to larger warehouse configurations with multiple bays. Pre-marshalling leverages off-peak time intervals to sort a block stacking warehouse in anticipation of future orders. These larger warehouse configurations require not only the minimization of the number of moves but also the consideration of distance or time when making sorting decisions. Our proposed solution for the multibay unit load pre-marshalling problem is based on our two-step approach that first determines the access direction for each stack and then finds a sequence of moves to sort the warehouse. In addition to adapting the existing approach that integrates a network flow model and an extended A* algorithm, we additionally present an exact constraint programming approach for the second stage of the problem-solving process. The results demonstrate that the presented solution approach effectively enhances the access time of unit loads and reduces the sorting effort for block stacking warehouses with multiple bays.

翻译：自主移动机器人（AMRs）正日益广泛地应用于内部物流的自动化操作。AMRs的关键特性之一是其高可用性，能够实现7×24小时不间断运行。本文研究了多bay单元载荷预分拣问题，将预分拣从单一bay扩展至包含多个bay的大型仓库配置。预分拣利用非高峰时段对块堆叠仓库进行排序，以应对未来订单需求。这类大型仓库配置不仅要求最小化货物移动次数，还要求在排序决策中考虑距离或时间因素。针对多bay单元载荷预分拣问题，我们提出的解决方案基于两步法：首先确定每个堆垛的访问方向，随后规划货物移动序列以完成仓库排序。除采用集成网络流模型与扩展A*算法的现有方法外，我们还在问题求解的第二阶段引入了一种精确约束规划方法。实验结果表明，所提方法有效提升了单元载荷的访问效率，并显著降低了多bay块堆叠仓库的排序工作量。